AIMC Topic: Adult

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An artificial intelligence algorithm for analyzing acetaminophen-associated toxic hepatitis.

Human & experimental toxicology
INTRODUCTION: Very little artificial intelligence (AI) work has been performed to investigate acetaminophen-associated hepatotoxicity. The objective of this study was to develop an AI algorithm for analyzing weighted features for toxic hepatitis afte...

Chronic cholestasis detection by a novel tool: automated analysis of cytokeratin 7-stained liver specimens.

Diagnostic pathology
BACKGROUND: The objective was to build a novel method for automated image analysis to locate and quantify the number of cytokeratin 7 (K7)-positive hepatocytes reflecting cholestasis by applying deep learning neural networks (AI model) in a cohort of...

Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial.

Nature medicine
We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a condition that is unde...

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

PloS one
In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-specific electroencephalographic (EEG) signatures of anesthesia-induced unconsciousness have been identi...

Evaluation of an open-source machine-learning tool to quantify bone marrow plasma cells.

Journal of clinical pathology
AIMS: The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive bone marrow plasma cells (BMPCs).

Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

JMIR mHealth and uHealth
BACKGROUND: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hosp...

The persuasive power of robot touch. Behavioral and evaluative consequences of non-functional touch from a robot.

PloS one
The unique physical embodiment of robots enables physical contact between machines and humans. Since interpersonal touch research has demonstrated that touch has several positive behavioral (e.g., reduced stress, better immune functioning) as well as...

Machine learning based models for prediction of subtype diagnosis of primary aldosteronism using blood test.

Scientific reports
Primary aldosteronism (PA) is associated with an increased risk of cardiometabolic diseases, especially in unilateral subtype. Despite its high prevalence, the case detection rate of PA is limited, partly because of no clinical models available in ge...

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.

BMC endocrine disorders
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...