AIMC Topic: Humans

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DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set.

Radiology
Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest radiographs might be useful for triage or infection control within a hospital s...

Automatic measurement of pressure ulcers using Support Vector Machines and GrabCut.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pressure ulcers are regions of trauma caused by a continuous pressure applied to soft tissues between a bony prominence and a hard surface. The manual monitoring of their healing evolution can be achieved by area assessment ...

Feed rate control in robotic bone drilling process.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The bone drilling process is characterised by various parameters, the most important of which are the feed rate (mm/s) and the drill speed (rpm). They highly reflect the final effects and results of the drilling process, such as mechanical and therma...

Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation? Using data mining artificial intelligence.

Chinese journal of traumatology = Zhonghua chuang shang za zhi
PURPOSE: The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse pr...

Natural language processing with deep learning for medical adverse event detection from free-text medical narratives: A case study of detecting total hip replacement dislocation.

Computers in biology and medicine
BACKGROUND: Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives can be challenging. Natural language processing (NLP) with deep learning has already shown great potential for analyzing free-text data, but i...

Identifying individuals with autism spectrum disorder based on the principal components of whole-brain phase synchrony.

Neuroscience letters
Autism spectrum disorder (ASD) is a brain disorder that develops during an early stage of childhood. Previous neuroimaging-based diagnostic models for ASD were based on static functional connectivity (FC). The nonlinear complexity of brain connectivi...

Design and rationale of an intelligent algorithm to detect BuRnoUt in HeaLthcare workers in COVID era using ECG and artificiaL intelligence: The BRUCEE-LI study.

Indian heart journal
BACKGROUND: There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associated with electrocardiographic changes detectable by artificial intelligence (AI).