AI Medical Compendium

Enabling the prediction of phage receptor specificity from genome data

bioRxiv Apr 19, 2026

Predicting which receptor a phage binds to from genome sequence alone has remained an intractable challenge, principally because the experimental phenotypic data required to train and validate predictive models have not been available at sufficient s... read more

microbiology

SCOPE: Integrating Organoid Screening and Clinical Variables Through Machine Learning for Cancer Trial Outcome Prediction

medRxiv Apr 18, 2026

BackgroundPredicting whether a treatment will demonstrate meaningful clinical benefit before committing to a large-scale trial remains a major unmet need in oncology. Patient-derived organoids (PDOs) recapitulate individual tumor drug sensitivity, bu... read more

oncology

Imbalance-Aware Optimal Transport Learning for Cost-Effective Diabetic Retinopathy Screening

medRxiv Apr 18, 2026

Abstract Background Diabetic Retinopathy (DR) is one of the leading cause of vision loss and blindness. AI models have been instrumental in providing an alternative solution to real-life medical treatment which are costly and sometimes not readily av... read more

ophthalmology

Robust prediction of Listeria monocytogenes, Listeria innocua and aerobic spoilage bacteria growth in food systems using Multilayer Perceptron Artificial Neural Networks.

International journal of food microbiology Apr 18, 2026

Spoilage microorganisms and pathogenic bacteria can negatively impact food safety and stability, leading to potential health risks and economic losses. Predictive microbiology is a crucial tool for forecasting microbial behavior in food matrices, and... read more

Integrated multi-omics data and machine learning approaches to decipher the molecular network and gene signatures of renal cell carcinoma induced by aristolochic acid.

Biochemical and biophysical research communications Apr 18, 2026

OBJECTIVE: This study aims to delineate the molecular mechanisms through which aristolochic acid (AA) exposure drives renal cell carcinoma (RCC) pathogenesis, leveraging an integrated machine learning (ML) and multi-omics approach to systematically i... read more

Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity.

European journal of radiology Apr 18, 2026

The AIXA Osteo model architecture (X1AI-Osteo) has undergone internal validation in Taiwan, demonstrating its capability to evaluate osteoporosis and predict T-scores reliably. Nonetheless, its efficacy in alternative clinical environments has not be... read more

Chicken disease detection and localization using multi-noise separation and acoustic recognition.

Poultry science Apr 18, 2026

Early detection and prevention of chicken disease are crucial for the sustainability of the poultry industry. However, early identification is often hindered by environmental noise and disease-specific acoustic feature extraction. This study proposes... read more

Development and Validation of Machine Learning Models to Identify Emergency Department Patients at Increased Risk of New or Progressive Acute Kidney Injury.

Journal of the American College of Emergency Physicians open Apr 18, 2026

OBJECTIVES: Acute kidney injury (AKI) is a common and serious condition associated with prolonged hospitalization, chronic kidney disease, and increased mortality. Early prediction of AKI offers an opportunity to mitigate these adverse outcomes, yet ... read more

Machine learning reveals drivers of microplastic bioaccumulation in fish from a freshwater reservoir ecosystem.

Environmental research Apr 18, 2026

Microplastics (MPs) are increasingly detected in freshwater ecosystems, yet the factors influencing their bioaccumulation in fish, particularly in reservoir systems, remain insufficiently understood. We investigated MPs bioaccumulation in 150 individ... read more

Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images.

Journal of dentistry Apr 18, 2026

OBJECTIVES: To develop a deep learning-based multi-class segmentation model for the simultaneous segmentation of key periodontal structures, including enamel, cementum, alveolar bone, and gingiva, in ultrasound images, and to enable precise localizat... read more

Artificial Intelligence Medical Compendium