AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Acute Disease

Showing 61 to 70 of 156 articles

Clear Filters

A different way to diagnosis acute appendicitis: machine learning.

Polski przeglad chirurgiczny
<b><br>Indroduction:</b> Machine learning is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention.</br> <b><br&g...

Comparison of an interpretable extreme gradient boosting model and an artificial neural network model for prediction of severe acute pancreatitis.

Polish archives of internal medicine
INTRODUCTION: Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as severe acute pancreatitis (SAP). It is a condition associated with a relatively high mortality. A prediction model that would facilitate early recogni...

Current use of artificial intelligence in the diagnosis and management of acute appendicitis.

Minerva surgery
INTRODUCTION: Acute appendicitis is a common and time-sensitive surgical emergency, requiring rapid and accurate diagnosis and management to prevent complications. Artificial intelligence (AI) has emerged as a transformative tool in healthcare, offer...

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Updates in surgery
Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and inter...

Deep learning-based radiomics of computed tomography angiography to predict adverse events after initial endovascular repair for acute uncomplicated Stanford type B aortic dissection.

European journal of radiology
PURPOSE: This study aimed to construct a predictive model integrating deep learning-derived radiomic features from computed tomography angiography (CTA) and clinical biomarkers to forecast postoperative adverse events (AEs) in patients with acute unc...

Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.

Scientific reports
This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cyto...

Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

The Israel Medical Association journal : IMAJ
BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral pharyngitis is sometimes difficult. Unnecessary antibiotic use contributes to unwanted side effects, such...

Leveraging machine learning for predicting acute graft-versus-host disease grades in allogeneic hematopoietic cell transplantation for T-cell prolymphocytic leukaemia.

BMC medical research methodology
Orphan diseases, exemplified by T-cell prolymphocytic leukemia, present inherent challenges due to limited data availability and complexities in effective care. This study delves into harnessing the potential of machine learning to enhance care strat...

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and im...

Artificial intelligence-based tools with automated segmentation and measurement on CT images to assist accurate and fast diagnosis in acute pancreatitis.

The British journal of radiology
OBJECTIVES: To develop an artificial intelligence (AI) tool with automated pancreas segmentation and measurement of pancreatic morphological information on CT images to assist improved and faster diagnosis in acute pancreatitis.