AIMC Topic: Middle Aged

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Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening.

Cancer research
UNLABELLED: Recent studies have reported increases in early-onset cancer cases (diagnosed less than 50 years of age) and raised questions about whether the increase is related to earlier diagnosis from nonspecific medical tests as reflected by decrea...

Multimodal Approach Predicts Relapse upon Cessation of Immune Checkpoint Inhibitors in Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Treatment with immune checkpoint inhibitors (ICI) in advanced melanoma can result in durable responses, yet an algorithm to decide which patients can safely discontinue ICI is still lacking.

Identifying azithromycin responders with an individual treatment effect model in COPD.

Thorax
OBJECTIVE: Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease (COPD). However, patients would benefit from better identification of responders and non-responders to minimise unnecessary ...

Exploring the impact of generative AI tools on healthcare delivery in Tanzania.

Journal of health organization and management
PURPOSE: This study explores the impact of generative AI tools on healthcare delivery in Tanzania. It examines its potential to enhance efficiency, accessibility and decision-making in health informatics while addressing infrastructure, ethics and eq...

Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Shear wave elastography (SWE) has been investigated as a complement to B-mode ultrasound for breast cancer diagnosis. Although multicenter trials suggest benefits for patients with Breast Imaging Reporting and Data System (BI-RADS) 4(a) brea...

Artificial intelligence and employee performance in Uganda's healthcare institutions: exploring the mediation effects of perceived ease of use and skills enhancement.

Journal of health organization and management
PURPOSE: The purpose of this study is to investigate the relationship between artificial intelligence (AI) and employee performance in Uganda's healthcare institutions, with a specific focus on exploring the mediating effects of perceived ease of use...

Detection of common bile duct dilatation on magnetic resonance cholangiopancreatography by deep learning.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: This study aims to detect common bile duct (CBD) dilatation using deep learning methods from artificial intelligence algorithms.

Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).

Predicting Urine Culture Outcomes in Adult Patients Using Machine Learning with the Aim of Reducing Unnecessary Urine Cultures.

The journal of applied laboratory medicine
BACKGROUND: Urine cultures are frequently ordered tests with a low positivity rate. Development of a machine learning model to predict urine culture outcomes could not only reduce unnecessary urine cultures but also prevent preliminary antibiotic tre...

Leveraging Hematologic Single-Cell Measurements for Patient Triage and Outcome Prediction.

The journal of applied laboratory medicine
BACKGROUND: The complete blood count (CBC) is widely used across nearly all areas of medicine. While standard CBC markers reflect basic summaries of the blood cells, modern hematology analyzers generate many additional markers from the underlying dat...