AIMC Topic: Humans

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Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.

BMC musculoskeletal disorders
BACKGROUND: Hip dysplasia is a condition where the acetabulum is too shallow to support the femoral head and is commonly considered a risk factor for hip osteoarthritis. The objective of this study was to develop a deep learning model to diagnose hip...

Proposing a Principle-Based Approach for Teaching AI Ethics in Medical Education.

JMIR medical education
The use of artificial intelligence (AI) in medicine, potentially leading to substantial advancements such as improved diagnostics, has been of increasing scientific and societal interest in recent years. However, the use of AI raises new ethical chal...

Conventional and deep learning methods in heart rate estimation from RGB face videos.

Physiological measurement
Contactless vital signs monitoring is a fast-advancing scientific field that aims to employ monitoring methods that do not necessitate the use of leads or physical attachments to the patient in order to overcome the shortcomings and limits of traditi...

Challenging the Chatbot: An Assessment of ChatGPT's Diagnoses and Recommendations for DBP Case Studies.

Journal of developmental and behavioral pediatrics : JDBP
OBJECTIVE: Chat Generative Pretrained Transformer-3.5 (ChatGPT) is a publicly available and free artificial intelligence chatbot that logs billions of visits per day; parents may rely on such tools for developmental and behavioral medical consultatio...

Exploring the Methodological Approaches of Studies on Radiographic Databases Used in Cariology to Feed Artificial Intelligence: A Systematic Review.

Caries research
INTRODUCTION: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different ...

Non-invasive load monitoring based on deep learning to identify unknown loads.

PloS one
With the rapid development of smart grids, society has become increasingly urgent to solve the problems of low energy utilization efficiency and high energy consumption. In this context, load identification has become a key element in formulating sci...

Machine learning-based prediction of hip joint moment in healthy subjects, patients and post-operative subjects.

Computer methods in biomechanics and biomedical engineering
The application of machine learning in the field of motion capture research is growing rapidly. The purpose of the study is to implement a long-short term memory (LSTM) model able to predict sagittal plane hip joint moment (HJM) across three distinct...

Automated detection of fatal cerebral haemorrhage in postmortem CT data.

International journal of legal medicine
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progress...

Classification of H. pylori Infection from Histopathological Images Using Deep Learning.

Journal of imaging informatics in medicine
Helicobacter pylori (H. pylori) is a widespread pathogenic bacterium, impacting over 4 billion individuals globally. It is primarily linked to gastric diseases, including gastritis, peptic ulcers, and cancer. The current histopathological method for ...