AIMC Topic: Middle Aged

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[Investigation of the impact of the deep learning based CT fractional flow reserve on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease].

Zhonghua xin xue guan bing za zhi
To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease. In this single-center retrospective cohort study, cons...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

Studies in health technology and informatics
The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of symptoms following the acute COVID-19 infection. The patient's baseline clinical features were used ...

Integrating Clinical Data and Patient-Reported Outcomes for Analyzing Gender Differences and Progression in Multiple Sclerosis Using Machine Learning.

Studies in health technology and informatics
Multiple sclerosis (MS) is a complex neurodegenerative disease with a variable prognosis that complicates effective management and treatment. This study leverages machine learning (ML) to enhance the understanding of disease progression and uncover g...

[Deep Learning Reconstruction Algorithm Combined With Smart Metal Artifact Reduction Technique Improves Image Quality of Upper Abdominal CT in Critically Ill Patients].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To evaluate the effect of deep learning reconstruction algorithm combined with smart metal artifact reduction (DLMAR) on the quality of abdominal CT images in critically ill patients who are unable to raise their arms and require electroca...

Universally Designed Augmented Reality as Interface for Artificial Intelligence Assisted Decision-Making in Everyday Life Scenarios.

Studies in health technology and informatics
This paper presents a conceptual prototype that integrates Artificial Intelligence (AI) and Augmented Reality (AR) with the principles of Universal Design (UD) to enhance decision-making in everyday scenarios for a diverse user base, eliminating the ...

High-dimensional Immune Profiles and Machine Learning May Predict Acute Myeloid Leukemia Relapse Early following Transplant.

Journal of immunology (Baltimore, Md. : 1950)
Identification of early immune signatures associated with acute myeloid leukemia (AML) relapse following hematopoietic stem cell transplant (HSCT) is critical for patient outcomes. We analyzed PBMCs from 58 patients with AML undergoing HSCT, focusing...

Hepatocellular Carcinoma Immune Microenvironment Analysis: A Comprehensive Assessment with Computational and Classical Pathology.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: The spatial variability and clinical relevance of the tumor immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). In this study, we aim to develop a deep learning (DL)-based image analysis model for t...

AI Prediction for Post-Lower Blepharoplasty Age Reduction.

Aesthetic surgery journal
BACKGROUND: Aesthetic standards vary and are subjective; artificial intelligence (AI), which is currently seeing a boom in interest, has the potential to provide objective assessment.

Gender and ethnicity bias in generative artificial intelligence text-to-image depiction of pharmacists.

The International journal of pharmacy practice
INTRODUCTION: In Australia, 64% of pharmacists are women but continue to be under-represented. Generative artificial intelligence (AI) is potentially transformative but also has the potential for errors, misrepresentations, and bias. Generative AI te...

Artificial intelligence enabled interpretation of ECG images to predict hematopoietic cell transplantation toxicity.

Blood advances
Artificial intelligence (AI)-enabled interpretation of electrocardiogram (ECG) images (AI-ECGs) can identify patterns predictive of future adverse cardiac events. We hypothesized that such an approach would provide prognostic information for the risk...