AI Medical Compendium

A causal AI and explainable optimization framework for social robot design.

iScience Apr 17, 2026

Mapping human-machine requirements in smart product design remains challenging. An integrated framework combining semiotic architecture product design (SAPAD), dual machine learning (DML), hesitant fuzzy quality function deployment (HFQFD), and multi... read more

How good are artificial intelligence tools at identifying benign skin lesions? A systematic review and meta-analysis of the specificity of artificial intelligence tools in diagnosing suspicious skin lesions.

Skin health and disease Apr 17, 2026

BACKGROUND: Artificial intelligence (AI) is a transformative diagnostic tool in dermatology. As the prevalence of skin cancer rises and pressure on health services increases, there is an increasing demand for efficient diagnostic tools. Therefore, it... read more

Deep learning and hyperspectral imaging for non-destructive amino acid detection in live carp fillets.

Food research international (Ottawa, Ont.) Apr 17, 2026

Rapid and non-destructive inspection of fillet nutritional quality is essential for selecting high-value live fish prior to processing, yet no such method exists for determining fillet amino acid (AA) contents. This study developed a non-destructive ... read more

Beyond saponins: An integrated mass spectrometry strategy for profiling, spatial mapping, and rapid authentication of non-saponin constituents in Panax species.

Food research international (Ottawa, Ont.) Apr 17, 2026

Non-saponin constituents of Panax species, including amino acids, sugars, and nucleosides, have attracted increasing attention due to their nutritional relevance and potential health benefits in food-medicine homologous materials. However, their high... read more

Development of a LightGBM-based survival prediction model for major burn patients using LDH/LYM ratio as the core predictor.

Burns : journal of the International Society for Burn Injuries Apr 17, 2026

BACKGROUND: Patients with extensive burns face a high mortality risk. Early identification of prognostic indicators may facilitate timely interventions that substantially improve outcomes and reduce mortality. The lactate dehydrogenase-to-lymphocyte ... read more

Spatial proteomics of tertiary lymphoid structures reveals correlation with immunotherapy response in Merkel cell carcinoma.

The British journal of dermatology Apr 17, 2026

BACKGROUND: Tertiary lymphoid structures (TLS) are ectopic lymphoid formations within or around tumours. They are emerging as important predictors of prognosis and response to immune checkpoint inhibitors (ICIs) in various cancers. However, in Merkel... read more

Learning from the past, structuring the future: using large language models to unlock a century of paediatric research in Archives of Disease in Childhood.

Archives of disease in childhood Apr 17, 2026

BACKGROUND AND AIMS: The centenary of Archives of Disease in Childhood (ADC) presents an opportunity to reflect on a century of paediatric research and consider how best to leverage this ever-growing repository for future use. While content is indexe... read more

Predicting CSR authenticity in healthcare organizations: an integrated SEM-IPMA-ANN approach through the lens of self-compassion theory.

Journal of health organization and management Apr 17, 2026

PURPOSE: As healthcare business organizations face mounting pressure from civil society to act responsibly, they are expanding and strategically restructuring their CSR activities. Under the umbrella of CSR, cause-related marketing (CRM) campaigns ar... read more

Vector2Variant: Discovery of Genetic Associations from ML Derived Representations without Phenotype Engineering

medRxiv Apr 17, 2026

Genome-wide association studies (GWAS) have transformed our understanding of human biology, but are constrained by the need for predefined phenotypes. We introduce Vector2Variant (V2V), a general-purpose framework that transforms any set of high-dime... read more

genetic and genomic medicine

Automated Detection of Dental Caries and Bone Loss on Periapical and Bitewing Radiographs using a YOLO Based Deep Learning Model