Artificial Intelligence Medical Compendium

Pretreatment prediction of neoadjuvant response remains an unresolved challenge in locally advanced rectal cancer, where management is moving towards risk-adapted and response-oriented treatment strategies. Prediction remains difficult because respon... read more 

The traditional drug discovery and development (DDD) pipeline has long been characterized by inefficiency and high costs. The rapid evolution of artificial intelligence (AI), especially AI-based toolkits for protein structure and interaction predicti... read more 

OBJECTIVE: Expert clinician chart review is the most accurate method to identify patients with infection but is laborious and costly. We aimed to develop and externally validate machine-learning models using structured and unstructured data to identi... read more 

Circulating tumor cells (CTCs), as pivotal targets in liquid biopsy, offer dynamic, multidimensional insights into tumor heterogeneity and metastatic progression. However, their extreme rarity, pronounced heterogeneity, and the complexity of the bloo... read more 

INTRODUCTION: Optimizing treatment adherence behaviour has become a focus in healthcare, as improved adherence enhances clinical outcomes, patient experiences and health system sustainability. For this optimization endeavour scholars have posited div... read more 

Identifying which gene drives a desired cell-state transition is a foundational inverse problem in target discovery and cell-state engineering, yet far less developed than forward prediction. We show that prevailing benchmarks inflate performance thr... read more 

Large-scale Neuropixels recordings sample many brain areas, but no single experimental session records every area of interest. NeuroPaint, a transformer-based autoencoder, integrates such recordings by aligning area-specific latent dynamics across se... read more 

Introduction: Early Alzheimer's disease (AD) staging remains challenging because clinical categories and global amyloid PET measures provide only coarse characterization of disease progression. We developed a continuous amyloid staging score from reg... read more 

In 1998 we predicted percent human intestinal absorption (HIA) for 86 drug and drug-like compounds from six molecular descriptors chosen by a genetic algorithm with a small neural network serving as the fitness function. That result rested on one div... read more 

We combine GeneNetwork's 1TB structured database with its metadata as an RDF graph and an associated literature corpus. We benchmark frontier and local LLMs querying it through four architectures: document, graph and agentic retrieval-augmented gener... read more