AI Medical Compendium

Quantification of hepatic steatosis on post-contrast computed tomography scans using artificial intelligence tools.

Abdominal radiology (New York) Jul 26, 2025

PURPOSE: Early detection of steatotic liver disease (SLD) is critically important. In clinical practice, hepatic steatosis is frequently diagnosed using computed tomography (CT) performed for unrelated clinical indications. An equation for estimating... read more

Hybrid modeling for optimizing electrospun polyurethane nanofibrous membranes in air filtration applications.

Scientific reports Jul 26, 2025

Nanofibers have gained recognition as promising materials for air filtration due to their high surface area-to-volume ratio, adjustable porosity, and exceptional mechanical properties. However, optimizing their structural characteristics to maximize ... read more

A comprehensive review of neural network-based approaches for drug-target interaction prediction.

Molecular diversity Jul 26, 2025

Predicting Drug-Target Interactions (DTI) is vital for accelerating drug discovery and repurposing. This review assesses the efficacy of neural network-based methods, including Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), and T... read more

Contextual structured annotations on PACS: a futuristic vision for reporting routine oncologic imaging studies and its potential to transform clinical work and research.

Abdominal radiology (New York) Jul 26, 2025

Radiologists currently have very limited and time-consuming options to annotate findings on the images and are mostly limited to arrows, calipers and lines to annotate any type of findings on most PACS systems. We propose a framework placing encoded,... read more

Multi-cohort machine learning identifies predictors of cognitive impairment in Parkinson's disease.

NPJ digital medicine Jul 26, 2025

Cognitive impairment is a frequent complication of Parkinson's disease (PD), affecting up to half of newly diagnosed patients. To improve early detection and risk assessment, we developed machine learning models using clinical data from three indepen... read more

External validation of a motion capture-based surgical skill assessment system in laparoscopic simulation training environments.

Surgical endoscopy Jul 26, 2025

PURPOSE: To externally validate our surgical skill assessment system, which provides comprehensive real-time feedback based on motion capture (Mocap) metrics of laparoscopic instruments in simulation training environments. read more

Machine Learning-Driven SERS Analysis Platform for Accurate and Rapid Diagnosis of Peritoneal Metastasis from Gastric Cancer.

Annals of surgical oncology Jul 26, 2025

BACKGROUND: Peritoneal metastasis (PM) is the most common form of distant metastasis in gastric cancer and is a major cause of mortality. Current diagnostic approaches suffer from low sensitivity, time-consuming procedures, and cannot provide real-ti... read more

Transforming label-efficient decoding of healthcare wearables with self-supervised learning and "embedded" medical domain expertise.

Communications engineering Jul 26, 2025

Healthcare wearables are transforming health monitoring, generating vast and complex data in everyday free-living environments. While supervised deep learning has enabled tremendous advances in interpreting such data, it remains heavily dependent on ... read more

Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.

Communications biology Jul 26, 2025

Understanding the pairing preferences and structural interactions between antibody heavy and light chains can enhance our ability to design more effective and specific therapeutic antibodies. Insights from natural antibody repertoires and conserved c... read more

A triple pronged approach for ulcerative colitis severity classification using multimodal, meta, and transformer based learning.