AIMC Topic: Retrospective Studies
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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...
Prediction Trough Concentrations of Valproic Acid Among Chinese Adult Patients with Epilepsy Using Machine Learning Techniques.
Pharmaceutical research
Jan 22, 2025
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict Valproic acid (VPA) trough concentrations in Chinese adult epilepsy patients.
Machine Learning-based Cluster Analysis Identifies Three Unique Phenotypes of Patients With Adult Spinal Deformity With Distinct Clinical Profiles and Long-term Recovery Trajectory: A Development Study.
Spine
Jan 21, 2025
STUDY DESIGN: A retrospective review of a prospective adult spinal deformity data.
Development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data: a protocol.
BMJ open
Jan 21, 2025
INTRODUCTION: Propofol is a widely used sedative-hypnotic agent for critically ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical benefits, propofol is associated with increased risks of hypertriglyceridemia. Early ide...
Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jan 21, 2025
BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significa...
Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.
Alzheimer's research & therapy
Jan 21, 2025
BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatme...
Developing a rapid screening tool for high-risk ICU patients of sepsis: integrating electronic medical records with machine learning methods for mortality prediction in hospitalized patients-model establishment, internal and external validation, and visualization.
Journal of translational medicine
Jan 21, 2025
OBJECTIVES: To develop a machine learning-based prediction model using clinical data from the first 24 h of ICU admission to enable rapid screening and early intervention for sepsis patients.
Deep learning-based CT radiomics predicts prognosis of unresectable hepatocellular carcinoma treated with TACE-HAIC combined with PD-1 inhibitors and tyrosine kinase inhibitors.
BMC gastroenterology
Jan 21, 2025
OBJECTIVE: To develop and validate a computed tomography (CT)-based deep learning radiomics model to predict treatment response and progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) treated with transarteri...
Humans
Prognosis
Adult
Radiomics
Male
Middle Aged
Deep Learning
Retrospective Studies
Tomography, X-Ray Computed
Female
Aged
Combined Modality Therapy
Chemoembolization, Therapeutic
Protein Kinase Inhibitors
Tyrosine Kinase Inhibitors
Liver Neoplasms
Carcinoma, Hepatocellular
Immune Checkpoint Inhibitors
Antineoplastic Combined Chemotherapy Protocols
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