AIMC Topic: Humans

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The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

AIDS and behavior
We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled National COVID Cohort Collaborative (N3C) data released from January 1, 2020 to October 10, 2022. We d...

Machine learning/artificial intelligence in sports medicine: state of the art and future directions.

Journal of ISAKOS : joint disorders & orthopaedic sports medicine
Machine learning (ML) is changing the way health care is practiced and recent applications of these novel statistical techniques have started to impact orthopaedic sports medicine. Machine learning enables the analysis of large volumes of data to est...

[The spring of artificial intelligence: AI vs. expert for internal medicine cases].

La Revue de medecine interne
INTRODUCTION: The "Printemps de la Médecine Interne" are training days for Francophone internists. The clinical cases presented during these days are complex. This study aims to evaluate the diagnostic capabilities of non-specialized artificial intel...

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

Gastroenterology
BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous perfo...

Who is responsible? US Public perceptions of AI governance through the lenses of trust and ethics.

Public understanding of science (Bristol, England)
The governance of artificial intelligence (AI) is an urgent challenge that requires actions from three interdependent stakeholders: individual citizens, technology corporations, and governments. We conducted an online survey ( = 525) of US adults to ...

Deep learning based detection of osteophytes in radiographs and magnetic resonance imagings of the knee using 2D and 3D morphology.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In this study, we investigated the discriminative capacity of knee morphology in automatic detection of osteophytes defined by the Osteoarthritis Research Society International atlas, using X-ray and magnetic resonance imaging (MRI) data. For the X-r...

AIEgen-deep: Deep learning of single AIEgen-imaging pattern for cancer cell discrimination and preclinical diagnosis.

Biosensors & bioelectronics
This study introduces AIEgen-Deep, an innovative classification program combining AIEgen fluorescent dyes, deep learning algorithms, and the Segment Anything Model (SAM) for accurate cancer cell identification. Our approach significantly reduces manu...

Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model.

Journal of imaging informatics in medicine
In intraoperative brain cancer procedures, real-time diagnosis is essential for ensuring safe and effective care. The prevailing workflow, which relies on histological staining with hematoxylin and eosin (H&E) for tissue processing, is resource-inten...

A macro-micro FE and ANN framework to assess site-specific bone ingrowth around the porous beaded-coated implant: an example with BOX® tibial implant for total ankle replacement.

Medical & biological engineering & computing
The use of mechanoregulatory schemes based on finite element (FE) analysis for the evaluation of bone ingrowth around porous surfaces is a viable approach but requires significant computational time and effort. The aim of this study is to develop a c...

The Role of Artificial Intelligence in Cardiac Imaging.

Radiologic clinics of North America
Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninva...