AIMC Topic: Retrospective Studies
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Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical features, serum tumor marker and imaging features.
Journal of cancer research and clinical oncology
Jun 17, 2025
BACKGROUND: With the improvement of imaging, the screening rate of Pulmonary nodules (PNs) has further increased, but their identification of High-Risk Prognostic Pathological Components (HRPPC) is still a major challenge. In this study, we aimed to ...
Machine learning strategies for multi-label pre-diagnosis of diseases with superficial data.
Computer methods and programs in biomedicine
Jun 16, 2025
BACKGROUND AND OBJECTIVE: General practice (GP) pre-diagnosis, a key task in disease triage, directs patients to suitable departments despite limited data and multi-label classification challenges. To address this issue, a framework with dimensionali...
Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jun 16, 2025
BACKGROUND: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world workflows due to operator-dependence of standardized image acquisition and incomplete view of breast ...
Application Value of Deep Learning-Based AI Model in the Classification of Breast Nodules.
British journal of hospital medicine (London, England : 2005)
Jun 15, 2025
Breast nodules are highly prevalent among women, and ultrasound is a widely used screening tool. However, single ultrasound examinations often result in high false-positive rates, leading to unnecessary biopsies. Artificial intelligence (AI) has dem...
Development and validation of a cardiac surgery-associated acute kidney injury prediction model using the MIMIC-IV database.
PloS one
Jun 12, 2025
OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify k...
A machine learning approach for personalized breast radiation dosimetry in CT: Integrating radiomics and deep neural networks.
European journal of radiology
Jun 11, 2025
PURPOSE: To develop a machine learning-based workflow for patient-specific breast radiation dosimetry in CT.
Evaluation of semi-automated versus fully automated technologies for computed tomography scalable body composition analyses in patients with severe acute respiratory syndrome Coronavirus-2.
Clinical nutrition ESPEN
Jun 11, 2025
RATIONALE AND OBJECTIVES: Fully automated, artificial intelligence (AI) -based software has recently become available for scalable body composition analysis. Prior to broad application in the clinical arena, validation studies are needed. Our goal wa...
Identification of neurological text markers associated with risk of stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jun 11, 2025
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...
Time Factors
Predictive Value of Tests
Natural Language Processing
Emergency Service, Hospital
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Stroke
Data Mining
Academic Medical Centers
Humans
Prognosis
Retrospective Studies
Reproducibility of Results
Risk Factors
Aged
Electronic Health Records
Female
Identifying patients at risk of increased health utilization following lumbar spine surgery.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 11, 2025
BACKGROUND: Adequate preoperative identification of patients at risk of significant healthcare utilization after surgery could help guide preoperative decision-making as well as postoperative patient management. While several studies have proposed me...
Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.
Journal of medical Internet research
Jun 11, 2025
BACKGROUND: The rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenues for managing complex clinical text data. However, the inherent complexity and specificity of medi...
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