AIMC Topic: Retrospective Studies
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AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.
Journal of medical Internet research
Jan 24, 2025
BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection...
Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.
Medical physics
Jan 23, 2025
BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, the manual fluence painting process presents a challenge for efficient clinical operation.
Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.
European radiology
Jan 23, 2025
OBJECTIVES: To assess glymphatic function and white matter integrity in children with autism spectrum disorder (ASD) using multi-parametric MRI, combined with machine learning to evaluate ASD detection performance.
Photoacoustic Imaging with Attention-Guided Deep Learning for Predicting Axillary Lymph Node Status in Breast Cancer.
Academic radiology
Jan 22, 2025
RATIONALE AND OBJECTIVES: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer management. This study explores the use of photoacoustic (PA) imaging combined with attention-guided deep learning (DL) for precise p...
Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.
International journal of medical informatics
Jan 22, 2025
BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogen...
Predicting Postoperative Infection After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy with Splenectomy.
Annals of surgical oncology
Jan 22, 2025
BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection afte...
A multimodal deep learning model for cervical pre-cancers and cancers prediction: Development and internal validation study.
Computers in biology and medicine
Jan 22, 2025
BACKGROUND: The current cervical cancer screening and diagnosis have limitations due to their subjectivity and lack of reproducibility. We describe the development of a deep learning (DL)-based diagnostic risk prediction model and evaluate its potent...
Death risk prediction model for patients with non-traumatic intracerebral hemorrhage.
BMC medical informatics and decision making
Jan 22, 2025
BACKGROUND: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage (ICH) using a machine learning model.
Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study.
BMC cancer
Jan 22, 2025
BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitat...
Development of a machine learning tool to predict deep inspiration breath hold requirement for locoregional right-sided breast radiation therapy patients.
Biomedical physics & engineering express
Jan 22, 2025
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...
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