AIMC Topic: Treatment Outcome

Clear Filters Showing 241 to 250 of 3204 articles

Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Aortic Aneurysm, Abdominal Elective Surgical Procedures Random Forest Endovascular Procedures Risk Assessment Time Factors Treatment Outcome Predictive Value of Tests Humans Machine Learning Algorithms Retrospective Studies Female Risk Factors Aged Aged, 80 and over Male Middle Aged
View on PubMed DOI

Influence of renal function on blood pressure control and outcome in thrombolyzed patients after acute ischemic stroke: analysis of the ENCHANTED trial.

Frontiers in endocrinology Dec 9, 2024
BACKGROUND: The effect of renal impairment in patients who receive intravenous thrombolysis for acute ischemic stroke (AIS) is unclear. We aimed to determine the associations of renal impairment and clinical outcomes and any modification of the effec...
Ischemic Stroke Middle Aged Humans Blood Pressure Female Kidney Thrombolytic Therapy Aged Hypertension Antihypertensive Agents Male Treatment Outcome Fibrinolytic Agents Glomerular Filtration Rate
View on PubMed DOI

Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation.

Trends in cardiovascular medicine Dec 7, 2024
Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting 2 % of the European population. This prevalence increases with age, imposing signif...
Predictive Value of Tests Stroke Atrial Fibrillation Stroke Rehabilitation Precision Medicine Humans Risk Factors Artificial Intelligence Risk Assessment Machine Learning Treatment Outcome Decision Support Techniques Recovery of Function
View on PubMed DOI

Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?

Journal of neurosurgery. Pediatrics Dec 6, 2024
OBJECTIVE: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6...
Humans Machine Learning Third Ventricle Child Female Treatment Outcome Male Hydrocephalus Infant Ventriculostomy Adolescent Neuroendoscopy Child, Preschool
View on PubMed DOI

Effectiveness of unilateral lower-limb exoskeleton robot on balance and gait recovery and neuroplasticity in patients with subacute stroke: a randomized controlled trial.

Journal of neuroengineering and rehabilitation Dec 5, 2024
BACKGROUND: Impaired balance and gait in stroke survivors are associated with decreased functional independence. This study aimed to evaluate the effectiveness of unilateral lower-limb exoskeleton robot-assisted overground gait training compared with...
Stroke Gait Exoskeleton Device Stroke Rehabilitation Gait Disorders, Neurologic Recovery of Function Robotics Postural Balance Single-Blind Method Humans Female Aged Adult Male Middle Aged Treatment Outcome Neuronal Plasticity Lower Extremity
View on PubMed DOI

Predictive utility of artificial intelligence on schizophrenia treatment outcomes: A systematic review and meta-analysis.

Neuroscience and biobehavioral reviews Dec 4, 2024
Identifying optimal treatment approaches for schizophrenia is challenging due to varying symptomatology and treatment responses. Artificial intelligence (AI) shows promise in predicting outcomes, prompting this systematic review and meta-analysis to ...
Humans Artificial Intelligence Treatment Outcome Schizophrenia
View on PubMed DOI

Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Journal of psychiatric research Dec 4, 2024
Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population...
Male Area Under Curve Outcome Assessment, Health Care Middle Aged Humans Stress Disorders, Post-Traumatic Aged Veterans Depression Machine Learning Outpatients ROC Curve Aged, 80 and over Latent Class Analysis Retrospective Studies Patient Health Questionnaire United States Young Adult Adolescent Female Treatment Outcome Adult Reproducibility of Results Mental Health Services
View on PubMed DOI

Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy.

Cell reports. Medicine Dec 4, 2024
Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of locally advanced gastric cancer. We propose an incremental supervised contrastive learning model (iSCLM), an interpretable artificial intelligence framew...
Male Middle Aged Humans Tomography, X-Ray Computed ROC Curve Artificial Intelligence Female Treatment Outcome Prognosis Aged Neoadjuvant Therapy Retrospective Studies Adult Stomach Neoplasms
View on PubMed DOI

Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

American journal of physical medicine & rehabilitation Dec 3, 2024
OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-assisted gait training in addition to traditional balance training, and traditional balance training alone on balance and fear of falling in patients ...
Humans Female Aged Male Middle Aged Gait Exercise Therapy Fear Stroke Rehabilitation Gait Disorders, Neurologic Accidental Falls Treatment Outcome Robotics Postural Balance Stroke
View on PubMed DOI

Artificial Intelligence-Driven Patient Selection for Preoperative Portal Vein Embolization for Patients with Colorectal Cancer Liver Metastases.

Journal of vascular and interventional radiology : JVIR Dec 3, 2024
PURPOSE: To develop a machine learning algorithm to improve hepatic resection selection for patients with metastatic colorectal cancer (CRC) by predicting post-portal vein embolization (PVE) outcomes.
Humans Reproducibility of Results Aged Adult Colorectal Neoplasms Male Machine Learning Decision Support Techniques Retrospective Studies Clinical Decision-Making Female Liver Regeneration Patient Selection Hepatectomy Embolization, Therapeutic Middle Aged Portal Vein Liver Neoplasms Patient-Specific Modeling Treatment Outcome Predictive Value of Tests
View on PubMed DOI
Popular Topics
Recent Journals