AI Medical Compendium

Multimodal fusion and explainability of artificial intelligence models in Alzheimer's Disease detection.

Brain informatics Feb 2, 2026

The integration of multimodal data has emerged as a powerful strategy for enhancing the accuracy and interpretability of artificial intelligence (AI) models in the diagnosis and prognosis of Alzheimer's Disease (AD). This systematic review presents a... read more

Interpretable machine learning unveils non-linear inflammatory thresholds and synergistic interactions in post-burn hypertrophic scarring: development of an intelligent clinical decision support system.

Scientific reports Feb 2, 2026

Hypertrophic scarring (HS) following severe burns remains a persistent rehabilitative challenge, yet traditional linear prediction models fail to capture the non-linear pathophysiological complexity of fibrosis. This study aimed to engineer an interp... read more

Improving precision agriculture using integrated bio-inspired optimization models for crop recommendation in Rajasthan, India.

Scientific reports Feb 2, 2026

This study introduces two novel hybrid nature-inspired optimization algorithms designed to enhance artificial neural network (ANN) performance in crop recommendation, leveraging remote sensing data from Landsat 8 and 9 platforms. The first hybrid app... read more

Pediatric coronary MR angiography with a two-minute scan using de-aliasing regularization based compressed sensing.

Magnetic resonance imaging Feb 2, 2026

BACKGROUND: Long acquisition time limits the clinical utility of coronary magnetic resonance angiography (CMRA) in pediatric populations. While deep learning-based reconstruction methods such as De-Aliasing Regularization-based Compressed Sensing (DA... read more

DeepVBM: A fully automatic and efficient voxel-based morphometry via deep learning-based segmentation and registration methods.

Magnetic resonance imaging Feb 2, 2026

Voxel-based morphometry (VBM) using T1-weighted magnetic resonance imaging is a pivotal tool for assessing brain structure and identifying subtle morphological changes associated with various neurological conditions. Conventional VBM workflows, howev... read more

Causal machine learning with interpretability deciphers the impact of micropollutants and socioeconomic factors on ARGs in Chinese urban drinking water.

Environmental research Feb 2, 2026

The widespread co-occurrence of antibiotic resistance genes (ARGs) with diverse micropollutants in drinking water distribution systems poses a critical public health threat by potentially facilitating ARG dissemination, yet the underlying causal driv... read more

Study design for an emulated trial of a 2 arm, parallel, stratified, adaptive, RCT of CABG versus PCI in people requiring myocardial revascularization at high risk (High-Risk REVASC).

American heart journal Feb 2, 2026

AIM: This study aims to use routinely collected health data and trial emulation methodology to inform the design of a pragmatic randomized controlled trial (RCT) in people requiring multivessel coronary revascularization with severe symptomatic multi... read more

RenoTrue: A diabetes-specific machine learning model to estimate glomerular filtration rate for people with diabetes.

Diabetes research and clinical practice Feb 2, 2026

BACKGROUND: Existing methods for estimating GFR in people with diabetes have shown inaccuracies when compared to mGFR measurements. We developed and validated an artificial neural network - RenoTrue to improve estimating GFR in people with diabetes. ... read more

Altered entropy modulation in bipolar disorder: EEG entropy measures during steady-state auditory entrainment.

Journal of affective disorders Feb 2, 2026

BACKGROUND: Non-linear neural dynamics reflect the inherent complexity of brain activity and are increasingly recognized as important indicators of neural adaptability and integrity. Bipolar disorder (BD) is associated with atypical brain activity, a... read more

Development of machine learning-driven non-invasive diagnostic models for idiopathic membranous nephropathy in Chinese patients.

Clinica chimica acta; international journal of clinical chemistry Feb 2, 2026

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a major cause of nephrotic syndrome and end-stage renal disease, but the gold-standard diagnostic method is invasive. This study aims to develop a non-invasive diagnostic model for IMN, focus on ... read more

Artificial Intelligence Medical Compendium