AIMC Topic: Humans

Clear Filters Showing 16171 to 16180 of 95995 articles

Large language models can accurately populate Vascular Quality Initiative procedural databases using narrative operative reports.

Journal of vascular surgery
OBJECTIVE: Participation in the Vascular Quality Initiative (VQI) provides important resources to surgeons, but the ability to do so is often limited by time and data entry personnel. Large language models (LLMs) such as ChatGPT (OpenAI) are examples...

A Fusion Model of MRI Deep Transfer Learning and Radiomics for Discriminating between Pilocytic Astrocytoma and Adamantinomatous Craniopharyngioma.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a fusion model combining MRI deep transfer learning (DTL) and radiomics for discriminating between pilocytic astrocytoma (PA) and adamantinomatous craniopharyngioma (ACP) in the sella...

Adaptive discrete-time neural prescribed performance control: A safe control approach.

Neural networks : the official journal of the International Neural Network Society
Most existing results on prescribed performance control (PPC), subject to input saturation and initial condition limitations, focus on continuous-time nonlinear systems. This article, as regards discrete-time nonlinear systems, is dedicated to constr...

Automated Bone Cancer Detection Using Deep Learning on X-Ray Images.

Surgical innovation
In recent days, bone cancer is a life-threatening health issue that can lead to death. However, physicians use CT-scan, X-rays, or MRI images to recognize bone cancer, but still require techniques to increase precision and reduce human labor. These m...

Machine Learning for In-hospital Mortality Prediction in Critically Ill Patients With Acute Heart Failure: A Retrospective Analysis Based on the MIMIC-IV Database.

Journal of cardiothoracic and vascular anesthesia
BACKGROUND: The incidence, mortality, and readmission rates for acute heart failure (AHF) are high, and the in-hospital mortality for AHF patients in the intensive care unit (ICU) is higher. However, there is currently no method to accurately predict...

Advances in deep learning for personalized ECG diagnostics: A systematic review addressing inter-patient variability and generalization constraints.

Biosensors & bioelectronics
The Electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its interpretation has traditionally relied on cardiologists' expertise. Deep learning has revolutionized medical data analysis, especially within ECG diagnostics. How...

Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC-MS urinary metabolomics for diseases screening.

International journal of medical informatics
BACKGROUND: Gas chromatography-mass spectrometry (GC-MS) has been shown to be a potentially efficient metabolic profiling platform in urine analysis. However, the widespread use of GC-MS for inborn errors of metabolism (IEM) screening is constrained ...

Noncontrast MRI-based machine learning and radiomics signature can predict the severity of primary lower limb lymphedema.

Journal of vascular surgery. Venous and lymphatic disorders
OBJECTIVE: According to International Lymphology Society guidelines, the severity of lymphedema is determined by the difference in volume between the affected limb and the healthy side divided by the volume of the healthy side. However, this method o...

Ethical and Bias Considerations in Artificial Intelligence/Machine Learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important considerations in our practice set...

Large Language Models Applied to Health Care Tasks May Improve Clinical Efficiency, Value of Care Rendered, Research, and Medical Education.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Large language models (LLMs) are generative artificial intelligence models that create content on the basis of the data on which it was trained. Processing capabilities have evolved from text only to being multimodal including text, images, audio, an...