AIMC Topic: Humans

Clear Filters Showing 29891 to 29900 of 95995 articles

How Appropriate Are Recommendations of Online Chat-Based Artificial Intelligence (ChatGPT) to Common Questions on Ventral Hernia Repair?

Journal of laparoendoscopic & advanced surgical techniques. Part A
ChatGPT is a conversational AI model developed by OpenAI to generate human-like text based on the input it receives. ChatGPT has become increasingly popular, and the general public may use this tool to ask questions about different medical conditions...

Artificial intelligence compared with human-derived patient educational materials on cirrhosis.

Hepatology communications
BACKGROUND: The study compared the readability, grade level, understandability, actionability, and accuracy of standard patient educational material against artificial intelligence chatbot-derived patient educational material regarding cirrhosis.

Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.

Scientific reports
In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed...

Investigation on explainable machine learning models to predict chronic kidney diseases.

Scientific reports
Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large proportion of the world's population and leading to higher morbidity and death rates. The early stages of CKD sometimes present without visible symptoms, causing pati...

A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.

Nature communications
Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based o...

InsightSleepNet: the interpretable and uncertainty-aware deep learning network for sleep staging using continuous Photoplethysmography.

BMC medical informatics and decision making
BACKGROUND: This study was conducted to address the existing drawbacks of inconvenience and high costs associated with sleep monitoring. In this research, we performed sleep staging using continuous photoplethysmography (PPG) signals for sleep monito...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

Journal for immunotherapy of cancer
BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it i...

Dexterous helical magnetic robot for improved endovascular access.

Science robotics
Treating vascular diseases in the brain requires access to the affected region inside the body. This is usually accomplished through a minimally invasive technique that involves the use of long, thin devices, such as wires and tubes, that are manuall...

Human-scale navigation of magnetic microrobots in hepatic arteries.

Science robotics
Using external actuation sources to navigate untethered drug-eluting microrobots in the bloodstream offers great promise in improving the selectivity of drug delivery, especially in oncology, but the current field forces are difficult to maintain wit...