AIMC Topic: Treatment Outcome
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Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair.
Journal of the American Heart Association
Mar 3, 2025
BACKGROUND: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remai...
Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers.
Nature communications
Mar 1, 2025
Cancer treatment has made significant advancements in recent decades, however many patients still experience treatment failure or resistance. Attempts to identify determinants of response have been hampered by a lack of tools that simultaneously acco...
Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study.
Scientific reports
Mar 1, 2025
This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPl...
Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity.
The bone & joint journal
Mar 1, 2025
AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction...
Clinical value of aortic arch morphology in transfemoral TAVR: artificial intelligence evaluation.
International journal of surgery (London, England)
Mar 1, 2025
BACKGROUND: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study w...
The use of artificial intelligence in psychotherapy: development of intelligent therapeutic systems.
BMC psychology
Feb 28, 2025
BACKGROUND: The increasing demand for psychotherapy and limited access to specialists underscore the potential of artificial intelligence (AI) in mental health care. This study evaluates the effectiveness of the AI-powered Friend chatbot in providing...
Effects of robot-assisted gait training within 1 week after stroke onset on degree of gait independence in individuals with hemiparesis: a propensity score-matched analysis in a single-center cohort study.
Journal of neuroengineering and rehabilitation
Feb 28, 2025
BACKGROUND: Robot-assisted gait training (RAGT) is an effective method for treating gait disorders in individuals with stroke. However, no previous studies have demonstrated the effectiveness of RAGT in individuals with acute stroke. This study aimed...
Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.
Breast cancer research : BCR
Feb 27, 2025
OBJECTIVE: The aim of this study was to develop and validate a deep learning radiomics (DLR) model based on longitudinal ultrasound data and clinical features to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breas...
Finding purpose: Integrated latent profile and machine learning analyses identify purpose in life as an important predictor of high-functioning recovery after alcohol treatment.
Addictive behaviors
Feb 25, 2025
BACKGROUND: Recent investigations of recovery from alcohol use disorder (AUD) have distinguished subgroups of high and low functioning recovery in data from randomized controlled trials of behavioral treatments for AUD. Analyses considered various in...
Comprehensive clinical scale-based machine learning model for predicting subthalamic nucleus deep brain stimulation outcomes in Parkinson's disease.
Neurosurgical review
Feb 25, 2025
Parkinson's Disease (PD) is a growing burden with varied clinical manifestations and responses to Subthalamic Nucleus Deep Brain Stimulation (STN-DBS). At present, there is no effective and simple machine learning model based on comprehensive clinica...
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