Biomedical physics & engineering express
Nov 29, 2024
This paper introduces a deep learning method for myocardial strain analysis while also evaluating the efficacy of the method across a public and a private dataset for cardiac pathology discrimination.We measure the global and regional myocardial stra...
BACKGROUND: Periodontitis (PD) is a common chronic inflammatory disease affecting the gums and supporting tooth structures. It is often diagnosed only after significant irreversible tissue damage - such as gum recession and bone loss - has occurred, ...
OBJECTIVES: This systematic review aimed to assess the effectiveness of Artificial Intelligence (AI)-based Deep Learning (DL) models in the detection of dental caries on intraoral images.
OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. We propose a deep learning (DL) method to reduce radiotracer dosage for PET studies while maintaining diagnostic quality.
The Anti-Nuclear Antibodies (ANA) test using Human Epithelial type 2 (HEp-2) cells in the Indirect Immuno-Fluorescence (IIF) assay protocol is considered the gold standard for detecting Connective Tissue Diseases. Computer-assisted systems for HEp-2 ...
BACKGROUND: The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the pat...
Monoclonal antibodies (mAbs) have found extensive applications and development in treating various diseases. From the pharmaceutical industry's perspective, the journey from the design and development of mAbs to clinical testing and large-scale produ...
INTRODUCTION: Diagnosing oral cancer is crucial in healthcare, with technological advancements enhancing early detection and outcomes. This review examines the impact of handheld AI-based tools, focusing on Convolutional Neural Networks (CNNs) and th...
: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Traditional methods rely on self-report questionnaires and clinical assessments, lacking objective biomarkers. Combining functional magnetic resonance imaging ...
This work aims to comprehensively explore the influencing factors of aerobics athletes' performance by integrating sports nutrition assistance and artificial intelligence neural networks. First, a personalized assessment and analysis of athletes' nut...
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