AI Medical Compendium

Transcriptome-based Deep Learning Model for Predicting Gemcitabine and Cisplatin Chemotherapy Response in Urothelial Carcinoma: Development and External Validation.

Cancer genomics & proteomics May 1, 2026

BACKGROUND/AIM: Chemotherapy with gemcitabine and cisplatin remains the cornerstone of treatment for advanced urothelial carcinoma (UC), yet response rates vary significantly among patients. Predicting treatment response is crucial to avoid unnecessa... read more

An XGBoost-Based Multicenter Model for Predicting HBV-Related Hepatocellular Carcinoma: Development and Validation.

Cancer medicine May 1, 2026

BACKGROUND: The 5-year survival rate for hepatocellular carcinoma (HCC) is stage-dependent, yet existing models lack accuracy in predicting hepatitis B virus-associated HCC (HBV-HCC). We therefore aimed to develop and validate an interpretable machin... read more

GPND-AI NULISA: A 15-Protein AI classifier for diagnosis and co-pathology profiling across neurodegenerative diseases.

Alzheimer's & dementia : the journal of the Alzheimer's Association May 1, 2026

INTRODUCTION: Accurate clinical diagnosis of neurodegenerative diseases remains challenging, particularly when individuals have mixed pathologies. We implemented the generalizable protein-based neurodegenerative disease artificial intelligence (GPND-... read more

From Low Field to High Value: Robust Cortical Mapping From Low-Field MRI.

Human brain mapping May 1, 2026

Three-dimensional reconstruction of cortical surfaces from MRI for subsequent morphometric analysis is fundamental for understanding brain structure. While high-field Magnetic Resonance Imaging (HF-MRI) is the standard in research and clinical settin... read more

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

Medical physics May 1, 2026

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lung adenocarcinoma is crucial for targeted therapy. Since EGFR mutations manifest as both macroscopic imaging features on CT and microscopic morphologi... read more

Spectral deep learning-based patient and bowtie scatter correction for clinical photon-counting CT.

Medical physics May 1, 2026

BACKGROUND: The presence of scatter in computed tomography degrades image quality, and can be caused by the patient and by other components in the beam path, such as the bowtie filter. While conventional energy-integrating detectors do not provide sp... read more

A Unified Framework for Statistical Inference and Power Analysis of Single and Comparative F β $$ {F}_{\beta } $$ Scores.

Statistics in medicine May 1, 2026

Machine learning and artificial intelligence are increasingly applied to medical diagnostics and clinical decision-making. To evaluate model performance, the F 1 $$ {F}_1 $$ score and its generalized form, the F β $$ {F}_{\beta } $$ score, ar... read more

Clinically Deployable Handwriting Biomarkers of Parkinson's Disease via Multiscale Attention and Bayesian-Genetic Optimization.

Brain and behavior May 1, 2026

INTRODUCTION: Subtle PD motor abnormalities can be underappreciated in examination but are overtly present in handwriting. Spiral, meander, and wave drawings are noninvasive, low-cost methods for capturing PD motor signatures and are easily collected... read more

Untargeted Metabolomics Coupled With Machine Learning Unravels Crop-Specific Versus Generalized Effects of Biostimulants in Cucumber, Pepper, and Tomato.

Physiologia plantarum May 1, 2026

In recent years, agricultural practices have shifted toward sustainability, aiming to reduce the use of agrochemicals and rely more on bio-based solutions. However, the effectiveness of these latter suffers from inconsistency. Understanding how diffe... read more

Hypoglycaemia Risk Prediction Models for Type 2 Diabetes: A Systematic Review and Meta-Analysis.

Endocrinology, diabetes & metabolism May 1, 2026

BACKGROUND: The growing number of hypoglycaemia risk prediction models for Type 2 diabetes mellitus (T2DM) underscores the need for systematic evaluation of their risk of bias and applicability. This study summarises and critically assesses their cha... read more

Artificial Intelligence Medical Compendium