AIMC Topic: Humans

Clear Filters Showing 19571 to 19580 of 95995 articles

Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation.

Journal of the American Heart Association
BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases bleeding risk, requiring personalization of DAPT duration. The aim of this study was to develop and validate a machine learning model to predict optim...

Deep Learning Virtual Contrast-Enhanced T1 Mapping for Contrast-Free Myocardial Extracellular Volume Assessment.

Journal of the American Heart Association
BACKGROUND: The acquisition of contrast-enhanced T1 maps to calculate extracellular volume (ECV) requires contrast agent administration and is time consuming. This study investigates generative adversarial networks for contrast-free, virtual extracel...

Predicting Intra- and Postpartum Hemorrhage through Artificial Intelligence.

Medicina (Kaunas, Lithuania)
: Intra/postpartum hemorrhage stands as a significant obstetric emergency, ranking among the top five leading causes of maternal mortality. The aim of this study was to assess the predictive performance of four machine learning algorithms for the pre...

Muscle Tone Assessment by Machine Learning Using Surface Electromyography.

Sensors (Basel, Switzerland)
Muscle tone is defined as the resistance to passive stretch, but this definition is often criticized for its ambiguity since some suggest it is related to a state of preparation for movement. Muscle tone is primarily regulated by the central nervous ...

Machine Learning-Empowered Real-Time Acoustic Trapping: An Enabling Technique for Increasing MRI-Guided Microbubble Accumulation.

Sensors (Basel, Switzerland)
Acoustic trap, using ultrasound interference to ensnare bioparticles, has emerged as a versatile tool for life sciences due to its non-invasive nature. Bolstered by magnetic resonance imaging's advances in sensing acoustic interference and tracking d...

Enhancing pap smear image classification: integrating transfer learning and attention mechanisms for improved detection of cervical abnormalities.

Biomedical physics & engineering express
Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through screening, such as Pap smear tests, is crucial for effective treatment and improved patient outcomes. How...

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...

Study on medical dispute prediction model and its clinical-application effectiveness based on machine learning.

BMC medical informatics and decision making
BACKGROUND: Medical dispute is a global public health issue, which has been garnering increasing attention. In this study, we used machine learning (ML) method to establish a dispute prediction model and explored the clinical-application efficiency o...

Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules.

BMC medical informatics and decision making
BACKGROUND: Patients undergo regular clinical follow-up after laminoplasty for cervical myelopathy. However, those whose symptoms significantly improve and remain stable do not need to conform to a regular follow-up schedule. Based on the 1-year post...

Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer.

BMC cancer
BACKGROUND: With the development of novel anti-HER2 targeted drugs, such as ADCs, it has become increasingly important to accurately interpret HER2 expression in breast cancer. Previous studies have demonstrated high intra-observer and inter-observer...