Latest AI and machine learning research in surveys for healthcare professionals.
The visual modality, i.e., images, plays a key role in multi-modal entity alignment (MMEA). Existing...
Background: Hypertension is the most important modifiable cardiovascular risk factor worldwide, and ...
Traditional scene understanding focuses on affirmative information objectively present in images. Ho...
Deep learning models for multi-modal breast cancer diagnosis achieve high predictive accuracy but re...
Reliable temporal-difference targets are central to off-policy actor-critic learning. Direct value i...
Background: Although iron-folic acid (IFA) supplementation is a known, low-cost intervention to prev...
Gender bias in large vision-language models (LVLMs) undermines their fairness and reliability, compr...
Medical AI models hold immense potential to improve patient outcomes, but they are also known to uni...
Detector response nonuniformity introduces systematic projection errors and ring artifacts in photon...
Rising societal and lifestyle complexity has been linked to a growing prevalence of mental distress ...
Answer accuracy alone cannot determine whether a Vision-Language Model (VLM) relies on clinically re...
Background: Nigeria's malaria burden is the highest in the world, both in terms of incidence and fat...
Evidence-synthesis teams increasingly depend on machine-learning tools to automate risk-of-bias asse...
Evolvable-Substrate HyperNEAT (ES-HyperNEAT), a bio-inspired indirect encoding that determines neuro...
Crash-severity models inform screening, dispatch and site prioritization, yet are deployed without a...
Background: There are two distinct failure points in childhood immunization: children who receive no...
Model pruning is widely used to compress deep neural networks, reducing memory and computational req...
Single-cell foundation models are increasingly adopted for downstream applications such as cell-type...
Semi-supervised learning has shown great potential for reducing annotation costs in medical image se...
Vision-language models (VLMs) are increasingly used to make decisions from visual inputs. We introdu...
Vision-language models are increasingly used to measure urban change from repeated street-level imag...