Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,381 to 1,390 of 234,892 articles

From code to cure: Harnessing AI for antibiotic discovery and design.

Science translational medicine
Artificial intelligence (AI) now enables the exploration of vast chemical and sequence spaces, the design of synthesizable antibiotics, and the prioritization of safe, mechanism-diverse candidates through integrated modeling and accelerated testing. ... read more 

DeepLNM: A Multimodal Model for Predicting Lymph Node Metastasis in Colorectal Cancer.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Accurate assessment of lymph node metastasis (LNM) is critical for prognostic stratification and treatment selection in colorectal cancer (CRC), yet imaging and routine pathology can yield false-negative/false-positive results. We propose DeepLNM, a ... read more 

Developing a generative AI chatbot to support students' higher-order thinking in STEM education.

Journal of microbiology & biology education
Higher-order thinking is a key component of science, technology, engineering, mathematics (STEM) reasoning and supports students' ability to reflect on their ideas, make connections, and generalize across contexts. We report a new approach to the use... read more 

Advancing early detection of Alzheimer's disease: from established biomarkers to future innovations.

International immunopharmacology
Alzheimer's disease (AD) is a major form of dementia, imposes an escalating global burden on public health and social care. Pathological changes in AD occur years before clinical symptoms, defining a prolonged preclinical phase. Currently, there is n... read more 

Predicting eating quality of pork shoulder butt using Vis/NIR hyperspectral imaging and machine learning models.

Meat science
This study proposed a framework for predicting eating quality clusters (EQCs) of pork shoulder butt using visible/near-infrared hyperspectral imaging (HSI). HSI data from 189 samples were acquired, and their EQCs were defined by applying k-means clus... read more 

Topology-aware dynamic co-evolution for robust graph learning.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have achieved remarkable success in learning from graph-structured data. However, recent studies have revealed their vulnerability to adversarial attacks, where imperceptible perturbations to the graph structure can easil... read more 

Machine learning-based prediction of hospital-acquired malnutrition at discharge using the GLIM criteria: A multicenter real-world study.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: This study aimed to investigate the incidence and clinical impact of hospital-acquired malnutrition (HAM) and develop a machine learning model for early risk prediction. METHODS: This secondary analysis included prospectively collected dat... read more 

Concentration of injury and fatality harm at repeat-active highway-rail grade crossings: A multi-state permutation and machine learning analysis.

Accident; analysis and prevention
Highway-rail grade crossing incidents remain a transportation safety concern, yet prior studies have focused mainly on crash occurrence, severity, and hotspot detection, leaving limited evidence on how injury-or-fatality harm concentrates at crossing... read more