AI Medical Compendium Topic:
Treatment Outcome

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Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study.

Psychopathology
BACKGROUND: New advances in the field of machine learning make it possible to track facial emotional expression with high resolution, including micro-expressions. These advances have promising applications for psychotherapy research, since manual cod...

Automated Detection of the Thoracic Ossification of the Posterior Longitudinal Ligament Using Deep Learning and Plain Radiographs.

BioMed research international
Ossification of the ligaments progresses slowly in the initial stages, and most patients are unaware of the disease until obvious myelopathy symptoms appear. Consequently, treatment and clinical outcomes are not satisfactory. This study is aimed at d...

Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety.

PloS one
In treating depression and anxiety, just over half of all clients respond. Monitoring and obtaining early client feedback can allow for rapidly adapted treatment delivery and improve outcomes. This study seeks to develop a state-of-the-art deep-learn...

Machine learning and decision making in aortic arch repair.

The Journal of thoracic and cardiovascular surgery
BACKGROUND: Decision making during aortic arch surgery regarding cannulation strategy and nadir temperature are important in reducing risk, and there is a need to determine the best individualized strategy in a data-driven fashion. Using machine lear...

Predicting Visual Acuity Responses to Anti-VEGF Treatment in the Comparison of Age-related Macular Degeneration Treatments Trials Using Machine Learning.

Ophthalmology. Retina
PURPOSE: To evaluate multiple machine learning (ML) models for predicting 2-year visual acuity (VA) responses to anti-vascular endothelial growth factor (anti-VEGF) treatment in the Comparison of Age-related Macular Degeneration (AMD) Treatments Tria...

Prognostication of Outcomes in Spontaneous Intracerebral Hemorrhage: A Propensity Score-Matched Analysis with Support Vector Machine.

World neurosurgery
OBJECTIVE: The role of surgery in spontaneous intracerebral hemorrhage (SICH) remains controversial. We aimed to use explainable machine learning (ML) combined with propensity-score matching to investigate the effects of surgery and identify subgroup...

Outcomes Comparison of Robot-Assisted and Video-Assisted Thoracoscopic Cardiac Sympathetic Denervation.

Innovations (Philadelphia, Pa.)
OBJECTIVE: Cardiac sympathetic denervation (CSD) is a surgical antiadrenergic procedure that can reduce sustained ventricular tachyarrhythmia (VT). Video-assisted thoracoscopic surgery (VATS) is currently the standard approach used in CSD, and the pr...

Robotic tomographic ultrasound and artificial intelligence for management of haemodialysis arteriovenous fistulae.

The journal of vascular access
BACKGROUND: Arteriovenous fistulae (AVF) and Arteriovenous Grafts (AVG) may present a problematic vascular access for renal replacement therapy (RRT), reliant on recurrent specialist nurse and medical evaluation. Dysfunctional accesses are frequently...

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients wi...

Robotic retroperitoneal lymph node dissection for paratesticular rhabdomyosarcoma in adolescents: a case series.

Journal of robotic surgery
Robotic assisted (RA) retroperitoneal lymph node dissection (RPLND) has grown in popularity as it offers decreased morbidity and faster recovery compared to the open technique. Proponents of open surgery raised concerns about the oncological fidelity...