Tech Xplore on MSN

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Ophthalmology Advisor

ChatGPT Update May Identify Glaucoma From Clinical Images

The ChatGPT o1 Pro can accurately identify glaucoma from visual field and optical coherence tomography data, a study shows.
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Scientific Research Publishing

Johnson, A. and Lee, M. (2022) Predictive Modeling for Cardiovascular Risk Assessment Using Logistic Regression and Deep Learning. Journal of Biomedical Informatics, 130 ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
IEEE

Automatic sleep and wake classifier with heart rate and pulse oximetry: Derived dynamic time warping features and logistic model

Abstract: This paper presents a novel sleep/wake classification method based on heart rate and pulse oximetry, using logistic model with derived dynamic time warping and correlation features ...
IEEE

A Hybrid CNN-Logistic Regression Model for Accurate Classification of Casting Defects

Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...
EurekAlert!

New few-shot learning model enhances crop disease recognition accuracy

Plant disease recognition technologies have advanced rapidly thanks to deep learning and large annotated datasets, but agricultural applications face unique hurdles. Data collection in the field is ...
WLRN

'95% accuracy': FIU researchers use artificial intelligence to detect heart disease early

FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...
Frontiers

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...
Frontiers

Machine learning-based classification model to differentiate subtypes of invasive breast cancer using MRI

1 Department of Radiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka 2 Department of Radiography/Radiotherapy, Faculty of Allied Health ...