AIMC Topic: Humans

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Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.

Proceedings of the National Academy of Sciences of the United States of America
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...

Mediation CNN (Med-CNN) Model for High-Dimensional Mediation Data.

International journal of molecular sciences
Complex biological features such as the human microbiome and gene expressions play a crucial role in human health by mediating various biomedical processes that influence disease progression, such as immune responses and metabolic processes. Understa...

stDyer enables spatial domain clustering with dynamic graph embedding.

Genome biology
Spatially resolved transcriptomics (SRT) data provide critical insights into gene expression patterns within tissue contexts, necessitating effective methods for identifying spatial domains. We introduce stDyer, an end-to-end deep learning framework ...

AI-powered standardised patients: evaluating ChatGPT-4o's impact on clinical case management in intern physicians.

BMC medical education
BACKGROUND: Artificial Intelligence is currently being applied in healthcare for diagnosis, decision-making and education. ChatGPT-4o, with its advanced language and problem-solving capabilities, offers an innovative alternative as a virtual standard...

Intracranial stenosis prediction using a small set of risk factors in the Tromsø Study.

BMC medical informatics and decision making
Intracranial atherosclerotic stenosis (ICAS) refers to a narrowing of intracranial arteries due to plaque buildup on the inside of the vessel walls restricting blood flow. Early detection of ICAS is crucial to prevent serious consequences such as str...

Exploring the capabilities of GenAI for oral cancer consultations in remote consultations : Author.

BMC oral health
BACKGROUND: Generative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer has not yet been fully evaluated. The objective of this study was to evaluate the accuracy, reliabil...

Optimized machine learning framework for cardiovascular disease diagnosis: a novel ethical perspective.

BMC cardiovascular disorders
Alignment of advanced cutting-edge technologies such as Artificial Intelligence (AI) has emerged as a significant driving force to achieve greater precision and timeliness in identifying cardiovascular diseases (CVDs). However, it is difficult to ach...

Pathology-based deep learning features for predicting basal and luminal subtypes in bladder cancer.

BMC cancer
BACKGROUND: Bladder cancer (BLCA) exists a profound molecular diversity, with basal and luminal subtypes having different prognostic and therapeutic outcomes. Traditional methods for molecular subtyping are often time-consuming and resource-intensive...

Personalised screening tool for early detection of sarcopenia in stroke patients: a machine learning-based comparative study.

Aging clinical and experimental research
BACKGROUND: Sarcopenia is a common complication in patients with stroke, adversely affecting recovery and increasing mortality risk. However, no standardised tool exists for its screening in this population. This study aims to identify factors influe...