AIMC Topic: Prognosis

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Prediction of Motor Function in Stroke Patients Using Machine Learning Algorithm: Development of Practical Models.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 19, 2021
BACKGROUND: Machine learning (ML) techniques are being increasingly adopted in the medical field.
Motor Activity Diagnosis, Computer-Assisted Deep Learning Time Factors Female Humans Logistic Models Reproducibility of Results Decision Support Techniques Aged Prognosis Male Retrospective Studies Middle Aged Recovery of Function Predictive Value of Tests Functional Status Stroke Extremities
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Survival prediction and treatment optimization of multiple myeloma patients using machine-learning models based on clinical and gene expression data.

Leukemia May 18, 2021
Multiple myeloma (MM) remains mostly an incurable disease with a heterogeneous clinical evolution. Despite the availability of several prognostic scores, substantial room for improvement still exists. Promising results have been obtained by integrati...
Prognosis Female Survival Rate Biomarkers, Tumor Male Humans Middle Aged Antineoplastic Combined Chemotherapy Protocols Machine Learning Gene Expression Profiling Follow-Up Studies Algorithms Cohort Studies Multiple Myeloma Gene Expression Regulation, Neoplastic
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Impact of ECG Characteristics on the Performance of an Artificial Intelligence Enabled ECG for Predicting Left Ventricular Dysfunction.

Circulation. Arrhythmia and electrophysiology May 17, 2021
Humans Artificial Intelligence Prognosis Retrospective Studies Heart Rate Female Ventricular Dysfunction, Left Middle Aged Reproducibility of Results Electrocardiography Aged Predictive Value of Tests Male Emergency Service, Hospital Ventricular Function, Left Signal Processing, Computer-Assisted
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Prognostic implications of body composition change during primary treatment in patients with ovarian cancer: A retrospective study using an artificial intelligence-based volumetric technique.

Gynecologic oncology May 14, 2021
OBJECTIVE: To investigate the impact of changes in body composition during primary treatment on survival outcomes in patients with epithelial ovarian cancer (EOC).
Body Composition Carcinoma, Ovarian Epithelial Intra-Abdominal Fat Subcutaneous Fat Deep Learning Cohort Studies Muscle, Skeletal Retrospective Studies Tomography, X-Ray Computed Female Middle Aged Humans Prognosis Ovarian Neoplasms Neoplasm Staging
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Deep recurrent model for individualized prediction of Alzheimer's disease progression.

NeuroImage May 13, 2021
Alzheimer's disease (AD) is known as one of the major causes of dementia and is characterized by slow progression over several years, with no treatments or available medicines. In this regard, there have been efforts to identify the risk of developin...
Magnetic Resonance Imaging Alzheimer Disease Neuropsychological Tests Disease Progression Deep Learning Cognitive Dysfunction Longitudinal Studies Humans Female Biomarkers Aged Prognosis Aged, 80 and over Male Middle Aged
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OASIS +: leveraging machine learning to improve the prognostic accuracy of OASIS severity score for predicting in-hospital mortality.

BMC medical informatics and decision making May 13, 2021
BACKGROUND: Severity scores assess the acuity of critical illness by penalizing for the deviation of physiologic measurements from normal and aggregating these penalties (also called "weights" or "subscores") into a final score (or probability) for q...
Humans Machine Learning Prognosis Retrospective Studies Hospital Mortality Intensive Care Units
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Hopes and Hypes for Artificial Intelligence in Colorectal Cancer Screening.

Gastroenterology May 11, 2021
Colorectal Neoplasms Colonoscopy Diagnosis, Computer-Assisted Early Detection of Cancer Predictive Value of Tests Humans Artificial Intelligence Prognosis Reproducibility of Results Diffusion of Innovation Image Interpretation, Computer-Assisted Observer Variation Overdiagnosis
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Assistance from Automated ASPECTS Software Improves Reader Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 11, 2021
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...
Radiographic Image Interpretation, Computer-Assisted Observer Variation Automation Middle Cerebral Artery Carotid Artery, Internal Magnetic Resonance Imaging Predictive Value of Tests Ischemic Stroke Radiologists Neurologists Software Prognosis Tomography, X-Ray Computed Female Reproducibility of Results Aged Humans Male Machine Learning Middle Aged Clinical Competence
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Spatio-temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity.

Human brain mapping May 10, 2021
The pathophysiology of major depressive disorder (MDD) has been explored to be highly associated with the dysfunctional integration of brain networks. It is therefore imperative to explore neuroimaging biomarkers to aid diagnosis and treatment. In th...
Depressive Disorder, Major Deep Learning Magnetic Resonance Imaging Connectome Nerve Net Humans Brain Prognosis Adult
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Machine Learning Can Predict Anti-VEGF Treatment Demand in a Treat-and-Extend Regimen for Patients with Neovascular AMD, DME, and RVO Associated Macular Edema.

Ophthalmology. Retina May 8, 2021
PURPOSE: To assess the potential of machine learning to predict low and high treatment demand in real life in patients with neovascular age-related macular degeneration (nAMD), retinal vein occlusion (RVO), and diabetic macular edema (DME) treated ac...
Macular Edema Vascular Endothelial Growth Factor A Intravitreal Injections Ranibizumab Wet Macular Degeneration Male Middle Aged Angiogenesis Inhibitors Follow-Up Studies Retinal Vein Occlusion Humans Diabetic Retinopathy Machine Learning Prognosis Retrospective Studies Female Aged Aged, 80 and over
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