AIMC Topic: Middle Aged
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PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma.
Nuclear medicine communications
May 6, 2025
OBJECTIVE: PET image analysis provides tumor heterogeneity data related to neoadjuvant chemotherapy response (NACR) and metastatic risk in osteosarcoma. Ki-67 expression is used to predict metastasis. The accuracy of prediction models with image quan...
Uncovering key factors in weight loss effectiveness through machine learning.
International journal of obesity (2005)
May 6, 2025
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Awareness, acceptance, and adoption of Gen-AI by K-12 mathematics teachers: an empirical study integrating TAM and TPB.
BMC psychology
May 6, 2025
In the 21st century, the variety of instructional media for mathematics has significantly diversified. Generative AI (Gen-AI) is one technology that K-12 teachers can utilize for teaching mathematics. However, as a new instructional medium, Gen-AI pr...
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.
BMC cancer
May 6, 2025
BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatment strategies. This study aimed to integrate radiomic features and clinical biomarkers through machin...
Exploring Therapists' Approaches to Treating Eating Disorders to Inform User-Centric App Design: Web-Based Interview Study.
JMIR formative research
May 6, 2025
BACKGROUND: The potential for digital interventions in self-management and treatment of mild to moderate eating disorders (EDs) has already been established. However, apps are infrequently recommended by ED therapists to their clients. Those that are...
AgeML: Age Modeling With Machine Learning.
IEEE journal of biomedical and health informatics
May 6, 2025
An approach to age modeling involves the supervised prediction of age using machine learning from subject features. The derived age metrics are used to study the relationship between healthy and pathological aging in multiple body systems, as well as...
Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma From Multi-Sequence Magnetic Resonance Imaging Based on Deep Fusion Representation Learning.
IEEE journal of biomedical and health informatics
May 6, 2025
Recent studies have identified microvascular invasion (MVI) as the most vital independent biomarker associated with early tumor recurrence. With advancements in medical technology, several computational methods have been developed to predict preopera...
Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.
Frontiers in cellular and infection microbiology
May 6, 2025
BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipterous larvae (maggots). However, bibliometric analysis of this disease remains sparse. Machine learn...
Interpretable Prognostic Modeling for Postoperative Pancreatic Cancer Using Multi-machine Learning and Habitat Radiomics: A Multi-center Study.
Academic radiology
May 5, 2025
RATIONALE AND OBJECTIVES: Accurate risk stratification is critical for guiding personalized treatment in resectable pancreatic cancer (RPC). This retrospective study assessed the utility of habitat radiomics for predicting recurrence-free survival (R...
Associations between the 24-h Activity Daily Cycle and Incident Dementia.
Medicine and science in sports and exercise
May 5, 2025
BACKGROUND: Physical activity, sedentary behavior (SB), and sleep all impact the risk of incident dementia, however, engagement in these activities is constrained by the 24-h day. Increasing time spent in one activity necessarily reduces time spent i...
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