AIMC Topic: Middle Aged

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Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Acute pancreatitis (AP) represents a critical medical condition where timely and precise prediction of in-hospital mortality is crucial for guiding optimal clinical management. This study focuses on the development of advanced machine lea...

Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images.

BMC medical imaging
BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical resection is crucial for effective tumor treatment. The choice of surgical approach is often challenging due to the low incidence and deep location. ...

Deep learning network enhances imaging quality of low-b-value diffusion-weighted imaging and improves lesion detection in prostate cancer.

BMC cancer
BACKGROUND: Diffusion-weighted imaging with higher b-value improves detection rate for prostate cancer lesions. However, obtaining high b-value DWI requires more advanced hardware and software configuration. Here we use a novel deep learning network,...

Prediction of coronary heart disease based on klotho levels using machine learning.

Scientific reports
The diagnostic accuracy for coronary heart disease (CHD) needs to be improved. Some studies have indicated that klotho protein levels upon admission comprise an independent risk factor for CHD and have clinical value for predicting CHD. This study ai...

Machine learning-driven imaging data for early prediction of lung toxicity in breast cancer radiotherapy.

Scientific reports
One possible adverse effect of breast irradiation is the development of pulmonary fibrosis. The aim of this study was to determine whether planning CT scans can predict which patients are more likely to develop lung lesions after treatment. A retrosp...

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.

Nature communications
Sepsis is a life-threatening organ dysfunction due to a dysfunctional response to infection. Delays in diagnosis have substantial impact on survival. Herein, blood samples from 586 in-house patients with suspected sepsis are used in conjunction with ...

Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

Annals of family medicine
PURPOSE: Increased workload associated with electronic visits (eVisits) in primary care could potentially be decreased by the use of artificial intelligence (AI); however, it is unknown whether this use of AI would be acceptable to staff and patients...

Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment.

Journal of medical Internet research
BACKGROUND: The integration of artificial intelligence (AI) holds substantial potential to alter diagnostics and treatment in health care settings. However, public attitudes toward AI, including trust and risk perception, are key to its ethical and e...

Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age.

Annals of family medicine
PURPOSE: Identifying cardiovascular disease before conception and in early pregnancy can better inform obstetric cardiovascular care. Our main objective was to evaluate the diagnostic performance of artificial intelligence (AI)-enabled digital tools ...

Development and validation of a CT-based radiomics machine learning model for differentiating immune-related interstitial pneumonia.

International immunopharmacology
INTRODUCTION: Immune checkpoint inhibitor-related interstitial pneumonia (CIP) poses a diagnostic challenge due to its radiographic similarity to other pneumonias. We developed a non-invasive model using CT imaging to differentiate CIP from other pne...