AIMC Topic: Humans

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Development and psychometric properties evaluation of nurses' innovative behaviours inventory in Iran: protocol for a sequential exploratory mixed-method study.

BMJ open
INTRODUCTION: Nurses' innovative behaviours play a crucial role in addressing the challenges including adapting to emerging technologies, resource limitations and social realities such as population ageing that are intricately tied to today's healthc...

Beyond integrative experiment design: Systematic experimentation guided by causal discovery AI.

The Behavioral and brain sciences
Integrative experiment design is a needed improvement over ad hoc experiments, but the specific proposed method has limitations. We urge a further break with tradition through the use of an enormous untapped resource: Decades of causal discovery arti...

Interactive segmentation of medical images using deep learning.

Physics in medicine and biology
Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount of labeled data. When performing pixel-level labeling on medical images, labeling a target requires ...

Deep learning-aided decision support for diagnosis of skin disease across skin tones.

Nature medicine
Although advances in deep learning systems for image-based medical diagnosis demonstrate their potential to augment clinical decision-making, the effectiveness of physician-machine partnerships remains an open question, in part because physicians and...

Attention-Based Deep Learning Model for Prediction of Major Adverse Cardiovascular Events in Peritoneal Dialysis Patients.

IEEE journal of biomedical and health informatics
Major adverse cardiovascular events (MACE) encompass pivotal cardiovascular outcomes such as myocardial infarction, unstable angina, and cardiovascular-related mortality. Patients undergoing peritoneal dialysis (PD) exhibit specific cardiovascular ri...

Detection and Assessment of Point-to-Point Movements During Functional Activities Using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist.

IEEE journal of biomedical and health informatics
Stoke is a leading cause of long-term disability, including upper-limb hemiparesis. Frequent, unobtrusive assessment of naturalistic motor performance could enable clinicians to better assess rehabilitation effectiveness and monitor patients' recover...

MAEF-Net: MLP Attention for Feature Enhancement in U-Net based Medical Image Segmentation Networks.

IEEE journal of biomedical and health informatics
Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has l...

An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice.

IEEE journal of biomedical and health informatics
General practice plays a prominent role in primary health care (PHC). However, evidence has shown that the quality of PHC is still unsatisfactory, and the accuracy of clinical diagnosis and treatment must be improved in China. Decision making tools b...

Automated Prediction of Infant Cognitive Development Risk by Video: A Pilot Study.

IEEE journal of biomedical and health informatics
OBJECTIVE: Cognition is an essential human function, and its development in infancy is crucial. Traditionally, pediatricians used clinical observation or medical imaging to assess infants' current cognitive development (CD) status. The object of pedi...

CellT-Net: A Composite Transformer Method for 2-D Cell Instance Segmentation.

IEEE journal of biomedical and health informatics
Cell instance segmentation (CIS) via light microscopy and artificial intelligence (AI) is essential to cell and gene therapy-based health care management, which offers the hope of revolutionary health care. An effective CIS method can help clinicians...