AIMC Topic: Humans

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Soul: An OCTA dataset based on Human Machine Collaborative Annotation Framework.

Scientific data
Branch retinal vein occlusion (BRVO) is the most prevalent retinal vascular disease that constitutes a threat to vision due to increased venous pressure caused by venous effluent in the space, leading to impaired visual function. Optical Coherence To...

The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center.

Scientific data
Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identi...

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

Journal of medical Internet research
BACKGROUND: Efforts are underway to capitalize on the computational power of the data collected in electronic medical records (EMRs) to achieve a learning health system (LHS). Artificial intelligence (AI) in health care has promised to improve clinic...

Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms.

BMC cardiovascular disorders
BACKGROUND: Patients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers.

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Scientific reports
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and...

MSRA-Net: multi-channel semantic-aware and residual attention mechanism network for unsupervised 3D image registration.

Physics in medicine and biology
. Convolutional neural network (CNN) is developing rapidly in the field of medical image registration, and the proposed U-Net further improves the precision of registration. However, this method may discard certain important information in the proces...

Towards robotic laboratory automation plug & play: Reference architecture model for robot integration.

SLAS technology
Supportive robotic solutions take over mundane, but essential tasks from human workforce in biomedical research and development laboratories. The newest technologies in collaborative and mobile robotics enable the utilization in the human-centered an...

Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events.

Pharmaceutical research
OBJECTIVE: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current...

Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer.