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AI applications in healthcare across the GCC — including medical imaging, clinical decision support, genomics, and health informatics from Gulf universities and hospitals.

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UAE thwarts terrorist cyberattacks targeting vital sectors - Arab News

Arab News News · · Policy Infrastructure

The UAE successfully thwarted several terrorist cyberattacks aimed at its vital sectors. These attacks targeted critical infrastructure and government services, with swift action preventing significant disruption or data breaches. Why it matters: This highlights the UAE's robust cybersecurity defenses and its commitment to protecting national security and critical infrastructure from advanced threats.

Nanoscale drug factory helps cells make medicine from within

KAUST · · Research Healthcare

Scientists at King Abdullah University of Science and Technology (KAUST) have engineered tiny metal-organic frameworks (MOFs) to deliver a team of six proteins into living cells. Inside the cells, these proteins formed a nanoscale factory that successfully produced violacein, a natural bioactive compound with therapeutic potential. This breakthrough represents the most complex multiprotein system delivered into living cells to date and the first example of a 'protein pathway transplant'. Why it matters: This research offers an early demonstration of how future therapies might generate treatment molecules directly inside the body at disease sites, potentially leading to more precise and less toxic medical interventions.

Professor Sahika Inal earns Germany’s most prestigious research award

KAUST · · Research Healthcare

Professor Sahika Inal from King Abdullah University of Science and Technology (KAUST) has been awarded the Alexander von Humboldt Professorship, Germany's most prestigious research award. The professorship, funded by the German Federal Ministry of Education and Research with up to €5 million, recognizes her leadership in next-generation bioelectronic materials and health technologies. She will establish a leading center for bioelectronic materials and devices in partnership with Dresden University of Technology and the Leibniz Institute of Polymer Research Dresden. Why it matters: This award underscores KAUST's research excellence in biomedical sciences and its faculty's global recognition, while fostering significant international collaboration in advanced health technologies.

AI tool helps detect pancreatic cancer up to three years before diagnosis, study finds - The National

The National · · Healthcare Research

An AI tool has reportedly been developed that can detect pancreatic cancer up to three years before a clinical diagnosis. This finding, based on a new study, was highlighted in a report by The National. The tool aims to significantly improve early detection capabilities for a challenging disease. Why it matters: Early and accurate detection of pancreatic cancer could lead to earlier interventions and substantially improve patient outcomes and survival rates.

AI to spot Alzheimer’s 20 years early? UAE researches shaping health care - PressReader

Gulf News News · · Healthcare Research

Based on the title, UAE researchers are exploring the application of artificial intelligence for the early detection of Alzheimer's disease. The research aims to identify the condition up to 20 years prior to the typical onset of symptoms, representing a significant advancement if achieved. This initiative underscores the UAE's strategic commitment to leveraging AI for major breakthroughs in healthcare. Why it matters: Such a breakthrough in ultra-early Alzheimer's detection could revolutionize preventative care and treatment strategies globally, offering an unprecedented window for intervention and disease management.

Severity-Aware Weighted Loss for Arabic Medical Text Generation

arXiv · · NLP LLM

Researchers proposed a severity-aware weighted loss method to fine-tune Arabic language models for medical text generation, prioritizing severe clinical cases. This approach utilizes soft severity probabilities, derived from an AraBERT-based classifier, to dynamically scale token-level loss contributions during optimization on the MAQA dataset. The method consistently improved performance across ten Arabic LLMs, with AraGPT2-Base increasing from 54.04% to 66.14% and AraGPT2-Medium from 59.16% to 67.18%. Why it matters: This novel fine-tuning strategy addresses a critical limitation in medical AI by enhancing the safety and reliability of Arabic medical large language models, particularly in high-stakes clinical scenarios.

Technology Innovation Institute Unveils 2 µm Fiber Laser for Medical and Industrial Use

TII · · Healthcare Product

The Technology Innovation Institute (TII) in Abu Dhabi has launched a 2-micrometer high-power fiber laser for medical and industrial applications. Developed by TII's Directed Energy Research Center, the Thulium-based laser is efficient, compact, and scalable, enabling precise interaction with water-rich materials. TII has partnered with LIMA Photonics, a German MedTech startup, to integrate the laser into clinical solutions, including urinary stone treatment and prostate surgery. Why it matters: This laser technology and partnership showcase the UAE's commitment to translating advanced research into healthcare solutions, positioning Abu Dhabi as a hub for medical technology innovation.

Advanced Technology Research Council Entities and ADAFSA Partner to Advance Sustainable Food and Agriculture Solutions in the Region

TII · · Partnership Research

The Advanced Technology Research Council (ATRC) entities ASPIRE and TII have partnered with the Abu Dhabi Agriculture and Food Safety Authority (ADAFSA) to advance sustainable food and agriculture solutions. The collaboration will focus on applied research activities in areas like diagnostics and therapeutics, sustainable protein, resilient water and energy solutions, and R&D initiatives. TII will participate through its Biotechnology Research Center (BRC), the Renewable and Sustainable Energy Research Center (RSERC), and the Advanced Materials Research Center (AMRC). Why it matters: This partnership signifies a strategic effort to leverage technology and research to enhance food security and environmental resilience in the UAE.

Technology Innovation Institute, Burjeel Medical City Partner to Advance Immunotherapy Solutions for Cancer Patients

TII · · Healthcare Research

Technology Innovation Institute (TII) and Burjeel Medical City (BMC) are partnering to develop novel immunotherapy solutions for cancer treatment, focusing on T-cell based therapeutics like CAR-T and TIL therapy. In the first phase, TII will construct a computational platform to identify patient-specific antigens from single-cell transcriptomics data, enabling the design of CAR-T cells. The two-year partnership aims to boost the body's immune system to fight cancer and personalize cancer therapies using TII's technologies. Why it matters: This collaboration signifies the UAE's commitment to advancing cancer care through collaborative research and innovative solutions, potentially establishing the country as a leader in personalized oncology treatments.

Technology Innovation Institute Launches Cutting-Edge Biofoundry to Advance R&D in Synthetic Biology

TII · · Research Partnership

The Technology Innovation Institute (TII) in Abu Dhabi has launched a Biofoundry to advance R&D in synthetic biology, focusing on genetic engineering, metabolic engineering, and bioinformatics. The facility features high-throughput robotic systems, next-generation sequencing, and advanced computational tools. TII's Biofoundry is now part of the Global Biofoundry Alliance (GBA) to foster partnerships and address shared challenges. Why it matters: This initiative positions the UAE as a key player in synthetic biology, with potential breakthroughs across healthcare, agriculture, and environmental sustainability.

Community-Based Early-Stage Chronic Kidney Disease Screening using Explainable Machine Learning for Low-Resource Settings

arXiv · · Research Healthcare

This paper introduces an explainable machine learning framework for early-stage chronic kidney disease (CKD) screening, specifically designed for low-resource settings in Bangladesh and South Asia. The framework utilizes a community-based dataset from Bangladesh and evaluates multiple ML classifiers with feature selection techniques. Results show that the ML models achieve high accuracy and sensitivity, outperforming existing screening tools and demonstrating strong generalizability across independent datasets from India, the UAE, and Bangladesh.

MMRINet: Efficient Mamba-Based Segmentation with Dual-Path Refinement for Low-Resource MRI Analysis

arXiv · · Research Healthcare

Researchers from MBZUAI have developed MMRINet, a Mamba-based neural network for efficient brain tumor segmentation in MRI scans. The model uses Dual-Path Feature Refinement and Progressive Feature Aggregation to achieve high accuracy with only 2.5M parameters, making it suitable for low-resource clinical environments. MMRINet achieves a Dice score of 0.752 and HD95 of 12.23 on the BraTS-Lighthouse SSA 2025 benchmark.

World-leading neurologist Professor Peter Goadsby appointed dean of new Division of Biomedical Sciences

KAUST · · Healthcare Research

Professor Peter Goadsby, a neurologist and neuroscientist, has been appointed as Senior Associate to the President and Founding Dean of KAUST's new Division of Biomedical Sciences. He will lead the establishment of the university's fourth academic division, focusing on Biomedical Sciences, and advance the neuroscience department. Goadsby's research identified CGRP as a central driver of migraine, leading to new medicines and earning him the 2021 Brain Prize. Why it matters: This appointment strengthens KAUST's and Saudi Arabia's capacity to translate research into healthcare solutions and supports the Kingdom’s Vision 2030 goals in health innovation.

Healing the land to feed the future

KAUST · · Research Partnership

KAUST researchers are using CarboSoil biochar and native biocrusts to revitalize arid lands in Saudi Arabia, enhancing soil fertility, capturing carbon, and reducing erosion. CarboSoil, engineered from poultry waste by KAUST's Himanshu Mishra, improves nutrient and water retention in desert soils. Terraxy, Mishra's startup, aims to convert all of Saudi Arabia's poultry waste into CarboSoil, supporting greening initiatives. Why it matters: This technology offers a sustainable solution to boost domestic food production, combat desertification, and reduce landfill waste in Saudi Arabia, aligning with the Kingdom's food security and environmental goals.

Red Sea study finds heat limits for clownfish-anemone partnership

KAUST · · Research Ecology

A KAUST-led study tracked clownfish and anemones in the Red Sea from 2022-2024, finding that extreme heat caused anemone bleaching, followed by near-total clownfish death, and then anemone death. The heatwave saw accumulated thermal stress reach 22 degrees heating weeks, far exceeding the threshold for coral bleaching. The research highlights heat risks faced by non-coral reef organisms and the need for taxon-specific thresholds to predict risks to reef symbiotic relationships. Why it matters: The Red Sea is a bellwether for climate change impacts on marine ecosystems, and this study underscores the urgency of conservation efforts like KAUST's Coral Restoration Initiative.

Scaling Arabic Medical Chatbots Using Synthetic Data: Enhancing Generative AI with Synthetic Patient Records

arXiv · · NLP LLM

Researchers address the challenge of limited Arabic medical dialogue data by generating 80,000 synthetic question-answer pairs using ChatGPT-4o and Gemini 2.5 Pro, expanding an initial dataset of 20,000 records. They fine-tuned five LLMs, including Mistral-7B and AraGPT2, and evaluated performance using BERTScore and expert review. Results showed that training with ChatGPT-4o-generated data led to higher F1-scores and fewer hallucinations across models. Why it matters: This demonstrates the potential of synthetic data augmentation to improve domain-specific Arabic language models, particularly for low-resource medical NLP applications.

Benchmarking the Medical Understanding and Reasoning of Large Language Models in Arabic Healthcare Tasks

arXiv · · NLP LLM

This paper benchmarks the performance of large language models (LLMs) on Arabic medical natural language processing tasks using the AraHealthQA dataset. The study evaluated LLMs in multiple-choice question answering, fill-in-the-blank, and open-ended question answering scenarios. The results showed that a majority voting solution using Gemini Flash 2.5, Gemini Pro 2.5, and GPT o3 achieved 77% accuracy on MCQs, while other LLMs achieved a BERTScore of 86.44% on open-ended questions. Why it matters: The research highlights both the potential and limitations of current LLMs in Arabic clinical contexts, providing a baseline for future improvements in Arabic medical AI.

New genetic maps expected to improve personalized medicine for underrepresented populations

KAUST · · Research Healthcare

KAUST, Tufts, and JIHS researchers created pangenome graphs using Saudi and Japanese samples, named JaSaPaGe. These graphs address the underrepresentation of these populations in existing pangenome databases, which are used as references for understanding individual DNA. The population-specific pangenomes are expected to improve variant calling and diagnostic accuracy for genetic disorders in these groups. Why it matters: This work promotes precision medicine and reduces diagnostic gaps for underrepresented populations by providing more relevant genetic baselines.

Saudi-based scientists lead global effort to combat land degradation and boost food security

KAUST · · Research Healthcare

A KAUST-led study in Nature proposes reversing land degradation by 2050 through increased sustainable seafood production, reduced food waste, and land restoration. The study suggests straightforward measures like modifying economic incentives and promoting sustainable aquaculture policies. Researchers estimate these policies could save a land area roughly the size of Africa. Why it matters: The KAUST-led research offers a tangible blueprint for addressing critical food security challenges in arid regions like Saudi Arabia and globally.

Deep learning accelerates research on early pregnancies

KAUST · · Research Healthcare

KAUST researchers have developed deepBlastoid, a deep learning tool for evaluating models of human embryo development, called blastoids. deepBlastoid can evaluate images of blastoids at speeds 1000 times faster than expert scientists, processing 273 images per second. Trained on over 2000 microscopic blastoid images, it assesses the impact of chemicals on blastoid development using over 10,000 images. Why it matters: This AI tool accelerates research into early pregnancy, fertility complications, and the impact of chemicals on embryo development, with implications for reproductive technologies.

MIRA: A Novel Framework for Fusing Modalities in Medical RAG

arXiv · · Research Healthcare

MBZUAI researchers have introduced MIRA, a novel framework for improving the factual accuracy of multimodal large language models in medical applications. MIRA uses calibrated retrieval to manage factual risk and integrates image embeddings with a medical knowledge base for efficient reasoning. Evaluated on medical VQA and report generation benchmarks, MIRA achieves state-of-the-art results, with code available on GitHub.

Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings

arXiv · · Healthcare Research

Researchers from MBZUAI introduce Forget-MI, a machine unlearning method tailored for multimodal medical data, enhancing privacy by removing specific patient data from AI models. Forget-MI utilizes loss functions and perturbation techniques to unlearn both unimodal and joint data representations. The method demonstrates superior performance in reducing Membership Inference Attacks and improving data removal compared to existing techniques, while preserving overall model performance and enabling data forgetting.

MOTOR: Multimodal Optimal Transport via Grounded Retrieval in Medical Visual Question Answering

arXiv · · Research NLP

This paper introduces MOTOR, a multimodal retrieval and re-ranking approach for medical visual question answering (MedVQA) that uses grounded captions and optimal transport to capture relationships between queries and retrieved context, leveraging both textual and visual information. MOTOR identifies clinically relevant contexts to augment VLM input, achieving higher accuracy on MedVQA datasets. Empirical analysis shows MOTOR outperforms state-of-the-art methods by an average of 6.45%.

KAUST develops nanotechnology that improves crop yields

KAUST · · Research Product

KAUST researchers have developed a hybrid cooling technology combining nanotech plastic and biodegradable mulch that significantly enhances crop yields in arid regions. The technology lowers greenhouse temperatures by 25 degrees Celsius and doubles crop yields in tests with Chinese cabbage. The nanotech plastic coating absorbs infrared light, while the biodegradable mulch reflects sunlight to keep the soil cooler. Why it matters: This innovation promises to improve food security in arid regions like Saudi Arabia while reducing energy consumption and plastic waste associated with traditional greenhouse cooling methods.

Saudi research institutes achieve record-breaking performance in data security

KAUST · · Research Partnership

Researchers from KAUST and KACST have developed a quantum random number generator (QRNG) that is almost 1000 times faster than existing QRNGs. The device utilizes micro-LEDs and advanced post-processing algorithms and has passed randomness tests by the National Institute of Standards and Technology. The QRNG's portability and high generation rate will benefit industries such as health, finance, and defense. Why it matters: This advancement significantly strengthens data security capabilities in Saudi Arabia, aligning with Vision 2030 goals for technological leadership and innovation.

Saudi health innovators accelerate smart health impact with KAUST’s experience

KAUST · · Healthcare Partnership

Saudi health innovators are increasing investment in smart health solutions, using KAUST's infrastructure and expertise. The King Salman Center for Disability Research (KSCDR) and KCSH are partnering on AI-based methods to identify genetic causes of rare eye diseases. KAUST and the Saudi Food and Drug Administration (SFDA) are expanding their agreement to enhance cooperation on AI and digital innovation. Why it matters: These partnerships signal a concerted effort to leverage AI for addressing critical healthcare challenges and advancing the Kingdom's health priorities.

Genetic secrets of rice pave way for future farming and conservation

KAUST · · Research Healthcare

KAUST researchers have published a study in Nature Genetics detailing genomic analysis of wild rice relatives. The study examined nine tetraploid and two diploid wild relatives of rice, finding significant genetic diversity due to transposable elements. This diversity includes genes that confer resilience to heat, drought, and salinity. Why it matters: These findings can help improve rice yields, introduce rice cultivation to currently untenable regions, and protect rice crops against climate change, especially in the Middle East.

MedNNS: Supernet-based Medical Task-Adaptive Neural Network Search

arXiv · · Research Healthcare

The paper introduces MedNNS, a neural network search framework designed for medical imaging, addressing challenges in architecture selection and weight initialization. MedNNS constructs a meta-space encoding datasets and models based on their performance using a Supernetwork-based approach, expanding the model zoo size by 51x. The framework incorporates rank loss and Fréchet Inception Distance (FID) loss to capture inter-model and inter-dataset relationships, improving alignment in the meta-space and outperforming ImageNet pre-trained DL models and SOTA NAS methods.

New discovery boosts wheat's fight against devastating disease

KAUST · · Research Healthcare

KAUST researchers have discovered the first molecular events that trigger wheat's immunity to stem rust, a devastating fungal disease. The study, published in Science, identifies that tandem kinases are bound together and inactive until a pathogen binds, initiating an immune response that kills the infected cell. This prevents the pathogen from spreading and causing widespread crop damage. Why it matters: Understanding these molecular mechanisms could lead to engineering wheat with stronger and more durable resistance to stem rust and other diseases, safeguarding a crucial food source in the face of climate change and emerging pathogens.

RP-SAM2: Refining Point Prompts for Stable Surgical Instrument Segmentation

arXiv · · CV Research

Researchers from MBZUAI introduced RP-SAM2, a method to improve surgical instrument segmentation by refining point prompts for more stable results. RP-SAM2 uses a novel shift block and compound loss function to reduce sensitivity to point prompt placement, improving segmentation accuracy in data-constrained settings. Experiments on the Cataract1k and CaDIS datasets show that RP-SAM2 enhances segmentation accuracy and reduces variance compared to SAM2, with code available on GitHub.

KAUST scientists see the first steps of life in DNA unwinding

KAUST · · Research Healthcare

KAUST researchers have captured the initial unwinding of DNA using cryo-electron microscopy and deep learning. The study details 15 atomic states describing how the Simian Virus 40 Large Tumor Antigen helicase unwinds DNA, revealing the coordinated roles of DNA, helicases, and ATP. The research elucidates the fundamental mechanisms of DNA replication, a cornerstone of growth and reproduction. Why it matters: This detailed understanding of helicase function could lead to advances in nanotechnology and our understanding of genetic processes.

SALT: Parameter-Efficient Fine-Tuning via Singular Value Adaptation with Low-Rank Transformation

arXiv · · Research Healthcare

Researchers introduce SALT, a parameter-efficient fine-tuning method for medical image segmentation that combines singular value adaptation with low-rank transformation. SALT selectively adapts influential singular values and complements this with a low-rank update for the remaining subspace. Experiments on five medical datasets show SALT outperforms state-of-the-art PEFT methods by 2-5% in Dice score with only 3.9% trainable parameters.

Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling

arXiv · · Research Healthcare

The paper introduces UAE-3D, a multi-modal VAE for 3D molecule generation that compresses molecules into a unified latent space, maintaining near-zero reconstruction error. This approach simplifies latent diffusion modeling by eliminating the need to handle multi-modality and equivariance separately. Experiments on GEOM-Drugs and QM9 datasets show UAE-3D establishes new benchmarks in de novo and conditional 3D molecule generation, with significant improvements in efficiency and quality.

KAUST scientists link gene to pediatric heart defects

KAUST · · Research Healthcare

KAUST researchers have identified the gene 'CIROZ' as responsible for pediatric heart defects and misplacement of internal organs, working with institutes in Saudi Arabia and worldwide. The research examined samples from 16 patients from 10 families, including four from Saudi Arabia, revealing CIROZ's role in embryonic development symmetry. The findings provide insights into heritable diseases, which are more prevalent in Saudi Arabia. Why it matters: Identifying this gene allows for focused research on preventative strategies and curative therapies for congenital heart defects, particularly relevant in regions with higher rates of such diseases.

Researchers crack nature’s code to coral resilience

KAUST · · Research Healthcare

KAUST researchers have discovered that a coral's resilience to rising temperatures is determined by the microorganisms living inside them. The study identifies specific combinations of microeukaryotes and bacteria that enhance heat resistance in corals. This finding provides valuable clues for developing coral probiotics to protect and restore coastal reefs. Why it matters: This breakthrough could lead to effective interventions to combat coral bleaching and preserve vital marine ecosystems in the Red Sea and beyond.

UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities

arXiv · · Healthcare Research

MBZUAI researchers introduce UniMed-CLIP, a unified Vision-Language Model (VLM) for diverse medical imaging modalities, trained on the new large-scale, open-source UniMed dataset. UniMed comprises over 5.3 million image-text pairs across six modalities: X-ray, CT, MRI, Ultrasound, Pathology, and Fundus, created using LLMs to transform classification datasets into image-text formats. UniMed-CLIP significantly outperforms existing generalist VLMs and matches modality-specific medical VLMs in zero-shot evaluations, improving over BiomedCLIP by +12.61 on average across 21 datasets while using 3x less training data.

BiMediX2: Bio-Medical EXpert LMM for Diverse Medical Modalities

arXiv · · LLM Healthcare

MBZUAI releases BiMediX2, a bilingual (Arabic-English) Bio-Medical Large Multimodal Model, along with the BiMed-V dataset (1.6M samples) and BiMed-MBench evaluation benchmark. BiMediX2 supports multi-turn conversation in Arabic and English and handles diverse medical imaging modalities. The model achieves state-of-the-art results on medical LLM and LMM benchmarks, outperforming existing methods and GPT-4 in specific evaluations.

Advancing Complex Medical Communication in Arabic with Sporo AraSum: Surpassing Existing Large Language Models

arXiv · · NLP LLM

A new study introduces Sporo AraSum, a language model designed for Arabic clinical documentation, and compares it to JAIS using synthetic datasets and modified PDQI-9 metrics. Sporo AraSum significantly outperformed JAIS in quantitative AI metrics and qualitative attributes related to accuracy, utility, and cultural competence. The model addresses the nuances of Arabic while reducing AI hallucinations, making it suitable for Arabic-speaking healthcare. Why it matters: The model offers a more culturally and linguistically sensitive solution for Arabic clinical documentation, potentially improving healthcare workflows and patient outcomes in the region.

Saudi could save millions with aquaculture technology

KAUST · · Research Partnership

KAUST and MEWA's Aquaculture Development Program (ADP) showcased achievements at the 6th International Saudi Aquaculture Development Workshop. New fish nutrition formulations developed by KAUST Beacon Development (KBD) could save Saudi Arabia $417 million per year in aquaculture production costs by 2030 through improved feed conversion ratios. KBD has also established complete production cycles for Sobaity and Gilthead seabream under Red Sea conditions. Why it matters: These advancements boost Saudi Arabia's food security and promote sustainable aquaculture, reducing reliance on imports and diversifying the economy in line with Vision 2030.

Saudi Arabia crater holds clues for extraterrestrial life

KAUST · · Research Healthcare

KAUST researchers have discovered biological clues in the Wahbah Crater in Saudi Arabia that could provide insights into the possibility of life on Enceladus, one of Saturn's moons. The researchers isolated 48 bacterial strains from the crater, identifying two with an adaptability suitable for the extreme environment of Enceladus. These strains thrive in high temperatures, salinity, and alkaline pH levels, mimicking conditions on the Saturn moon. Why it matters: This study highlights the potential of Saudi Arabia's extreme environments as valuable models for detecting extraterrestrial life and strengthens the country's growing interest in space exploration.

Oxford Nanopore Technologies collaboration advances multi-omics research

KAUST · · Partnership Research

KAUST and Oxford Nanopore Technologies have signed an MoU to collaborate on multi-omics research, building on previous work such as the NanoRanger technique developed by KAUST's Mo Li. KAUST will gain early access to Oxford Nanopore’s sequencing technology, while Oxford Nanopore will access KAUST's Core Labs. Why it matters: This partnership enhances KAUST's research capabilities in areas like rare diseases and desert agriculture, and provides Oxford Nanopore with a launchpad to engage with Saudi Arabia's research community.

KAUST launches four pioneering Centers of Excellence to address key national priorities

KAUST · · Research Partnership

KAUST has launched four Centers of Excellence (CoEs) focusing on Health, Sustainable Environment, Energy, and Economies of the Future, aligning with Saudi Arabia’s Vision 2030. One CoE, chaired by Professor Bernard Ghanem and co-chaired by Professor Juergen Schmidhuber, will focus on generative AI. These centers aim to deliver impactful solutions that directly contribute to national economic objectives. Why it matters: This initiative signifies a major push towards applied AI research and development within Saudi Arabia, particularly in generative AI, renewable energy, food security, and smart health.

KAUST Center of Excellence for Sustainable Food Security

KAUST · · Research Partnership

KAUST has launched a Center of Excellence for Sustainable Food Security, led by Professor Mark Tester. The center aims to develop innovative solutions for food security challenges in arid regions, aligning with Saudi Vision 2030. It will focus on enhancing resource use efficiency, developing resilient crops, and promoting sustainable biosystems through interdisciplinary research and partnerships. Why it matters: This initiative will advance agricultural innovation in Saudi Arabia, supporting economic diversification and reducing reliance on food imports.

Weeds like a certain gene in an important Saudi crop

KAUST · · Research Healthcare

KAUST researchers have identified a gene, CLAMT1b, in pearl millet that affects its vulnerability to the parasitic weed Striga hermonthica. Pearl millet strains lacking CLAMT1b were found to be resistant to the weed, while those expressing the gene were susceptible. The gene's presence leads to the secretion of strigolactones, promoting interaction with Striga, but its absence does not harm symbiotic relationships with beneficial fungi. Why it matters: This discovery offers new breeding strategies to enhance pearl millet's resistance to parasitic weeds, bolstering food security in arid regions like Saudi Arabia and Africa where the crop is vital.

Unravelling the secrets of modern wheat genetics

KAUST · · Research Healthcare

KAUST researchers have developed a genomic resource for Tausch’s goatgrass (Aegilops tauschii), a wild relative of wheat, by creating 46 high-quality genome assemblies. They compiled 493 genetically distinct accessions from an initial 900, collaborating with the Open Wild Wheat Consortium to select accessions with traits of interest, such as disease resistance and stress tolerance. Screening these assemblies helped identify rust resistance genes, including mapping a stem rust resistance gene to the Sr33 locus. Why it matters: This genomic resource will accelerate gene discovery in wheat, potentially improving modern wheat varieties and enhancing global food security.

KAUST researchers are Gordon Bell finalist

KAUST · · Research Partnership

KAUST researchers have been selected as finalists for two ACM Gordon Bell Prizes for high-performance computing. One project used NVIDIA GPUs to enhance genetic studies from the UK Biobank, achieving 133x speedup over existing software. The other developed an exascale climate emulator with higher spatial-temporal resolution than current models, demonstrated on supercomputers like Shaheen III. Why it matters: The recognition highlights KAUST's strength in high-performance computing research and its contributions to both genetic analysis and climate modeling.

KAUST gene sequencing technology gives new hope to patients

KAUST · · Healthcare Research

KAUST and KFSHRC have developed NanoRanger, a new gene sequencing system for identifying mutations causing genetic diseases. NanoRanger offers a faster and simpler process to detect DNA abnormalities at base resolution, building on existing long-read sequencing technologies. The system is designed to be cheaper and faster, targeting diseases prevalent in Saudi Arabia due to consanguinity. Why it matters: The technology has the potential to improve diagnosis and treatment of Mendelian diseases, which are especially prevalent in the Arab world.

Transforming the future of Saudi aquaculture through KAUST’s partnership with MEWA

KAUST · · Partnership Research

KAUST and the Saudi Ministry of Environment, Water and Agriculture (MEWA) are collaborating on the Aquaculture Development Program (ADP) to advance Saudi Arabia's food security goals under Vision 2030. The ADP aims to increase domestic seafood production to 530,000 tons annually by 2030 through sustainable aquaculture practices. KAUST is employing a multidisciplinary team and innovative approaches like Integrated Multitrophic Aquaculture (IMTA) to optimize resource use and minimize environmental impact. Why it matters: This partnership aims to transform Saudi Arabia's aquaculture sector, reducing reliance on imports and promoting economic diversification while preserving marine biodiversity.

A rare discovery in the Red Sea hints at how life first formed

KAUST · · Research Healthcare

KAUST researchers discovered a five-hectare bio-sedimentary formation of living stromatolites off Sheybarah Island in the Red Sea. These structures are microbial carbonates similar to fossils of early life and are only the second group found in normal marine settings. The stromatolites host a diverse microbial community, including reticulated filaments previously only found in caves. Why it matters: The discovery provides insights into early life on Earth and has implications for understanding potential life formation on Mars, while also creating a unique educational opportunity for tourism in Saudi Arabia.

Continual Learning in Medical Imaging: A Survey and Practical Analysis

arXiv · · Research Healthcare

This survey paper reviews recent literature on continual learning in medical imaging, addressing challenges like catastrophic forgetting and distribution shifts. It covers classification, segmentation, detection, and other tasks, while providing a taxonomy of studies and identifying challenges. The authors also maintain a GitHub repository to keep the survey up-to-date with the latest research.