AIMC Topic: Humans

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Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions.

Journal of thrombosis and haemostasis : JTH
Artificial Intelligence and machine-learning (ML) studies are increasingly populating the life science space and some have also started to integrate certain clinical decision support tasks. However, most of the activities within this space understand...

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

Journal of applied clinical medical physics
PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment.

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle.

Clinical imaging
OBJECTIVE: In this study, we investigate the feasibility of a deep Convolutional Neural Network (dCNN), trained with mammographic images, to detect and classify microcalcifications (MC) in breast-CT (BCT) images.

Multi-task deep learning for medical image computing and analysis: A review.

Computers in biology and medicine
The renaissance of deep learning has provided promising solutions to various tasks. While conventional deep learning models are constructed for a single specific task, multi-task deep learning (MTDL) that is capable to simultaneously accomplish at le...

Diagnosis of arrhythmias with few abnormal ECG samples using metric-based meta learning.

Computers in biology and medicine
A major challenge in artificial intelligence based ECG diagnosis lies that it is difficult to obtain sufficient annotated training samples for each rhythm type, especially for rare diseases, which makes many approaches fail to achieve the desired per...

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing.

Computers in biology and medicine
Pre-processing is widely applied in medical image analysis to remove the interference information. However, the existing pre-processing solutions mainly encounter two problems: (i) it is heavily relied on the assistance of clinical experts, making it...

Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images.

Computers in biology and medicine
Understanding prognosis and mortality is critical for evaluating the treatment plan of patients. Advances in digital pathology and deep learning techniques have made it practical to perform survival analysis in whole slide images (WSIs). Current meth...

Deep learning reveals what vocal bursts express in different cultures.

Nature human behaviour
Human social life is rich with sighs, chuckles, shrieks and other emotional vocalizations, called 'vocal bursts'. Nevertheless, the meaning of vocal bursts across cultures is only beginning to be understood. Here, we combined large-scale experimental...