AIMC Topic: Predictive Value of Tests

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Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.

JAMA network open Dec 1, 2020
IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant-positive non-small cell lung cancer (...
Prognosis Female Male Middle Aged Antineoplastic Agents Survival Analysis Humans Machine Learning Proportional Hazards Models ErbB Receptors Protein Kinase Inhibitors Antineoplastic Protocols Lung Neoplasms Carcinoma, Non-Small-Cell Lung Predictive Value of Tests Neoplasm Staging Mutation
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Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Nov 30, 2020
BACKGROUND: For the growing patient population with congenital heart disease (CHD), improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are considered unmet clinical needs. Cardiovascular magnetic resonance (CMR) imaging of...
Workflow Child, Preschool Humans Child Female Image Interpretation, Computer-Assisted Age Factors Automation Reproducibility of Results Magnetic Resonance Imaging Heart Defects, Congenital Male Predictive Value of Tests Deep Learning Adolescent
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Using Artificial Intelligence to Predict Change in Depression and Anxiety Symptoms in a Digital Intervention: Evidence from a Transdiagnostic Randomized Controlled Trial.

Psychiatry research Nov 29, 2020
While digital psychiatric interventions reduce treatment barriers, not all persons benefit from this type of treatment. Research is needed to preemptively identify who is likely to benefit from these digital treatments in order to redirect those peop...
Follow-Up Studies Predictive Value of Tests Evidence-Based Medicine Adult Therapy, Computer-Assisted Humans Male Artificial Intelligence Middle Aged Female Depressive Disorder, Major Young Adult Anxiety Disorders
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Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER.

CNS neuroscience & therapeutics Nov 28, 2020
AIMS: Coagulation abnormality is one of the primary concerns for patients with spontaneous intracerebral hemorrhage admitted to ER. Conventional laboratory indicators require hours for coagulopathy diagnosis, which brings difficulties for appropriate...
Predictive Value of Tests Emergency Service, Hospital Blood Coagulation Disorders Humans Adult Machine Learning Male Algorithms Middle Aged Retrospective Studies Cohort Studies Female Cerebral Hemorrhage Aged
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Machine learning algorithm for early detection of end-stage renal disease.

BMC nephrology Nov 27, 2020
BACKGROUND: End stage renal disease (ESRD) describes the most severe stage of chronic kidney disease (CKD), when patients need dialysis or renal transplant. There is often a delay in recognizing, diagnosing, and treating the various etiologies of CKD...
Machine Learning Algorithms Databases, Factual Prognosis Female Male Middle Aged Disease Progression ROC Curve Logistic Models Humans Renal Insufficiency, Chronic Predictive Value of Tests Kidney Failure, Chronic Early Diagnosis
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Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study.

Gastrointestinal endoscopy Nov 26, 2020
BACKGROUND AND AIMS: Narrow-band imaging with magnifying endoscopy (ME-NBI) has shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in diagnostic algorithms requires substantial expertise and experience. In this stud...
Deep Learning Early Detection of Cancer Predictive Value of Tests Narrow Band Imaging Humans Stomach Neoplasms
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Machine Learning-Based Risk Assessment for Cancer Therapy-Related Cardiac Dysfunction in 4300 Longitudinal Oncology Patients.

Journal of the American Heart Association Nov 26, 2020
Background The growing awareness of cardiovascular toxicity from cancer therapies has led to the emerging field of cardio-oncology, which centers on preventing, detecting, and treating patients with cardiac dysfunction before, during, or after cancer...
Antineoplastic Agents ROC Curve Predictive Value of Tests Cardiotoxicity Humans Machine Learning Algorithms Retrospective Studies Female Aged Male Middle Aged Risk Assessment Neoplasms
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Training confounder-free deep learning models for medical applications.

Nature communications Nov 26, 2020
The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variab...
Sex Characteristics Sex Factors Image Interpretation, Computer-Assisted Datasets as Topic Age Determination by Skeleton Magnetic Resonance Imaging Predictive Value of Tests Radiography Hand Adult Male Middle Aged Case-Control Studies Deep Learning Adolescent HIV Infections Brain Cohort Studies Female Humans Child Aged Age Factors Aged, 80 and over Young Adult
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Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

The international journal of cardiovascular imaging Nov 23, 2020
We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic and echocardiographic parameters, could enhance the appraisal of the likelihood of reverse remodeling and prognosis of favorable clinical evolution to...
Machine Learning Decision Support Techniques Retrospective Studies Female Aged Humans Electrocardiography Treatment Outcome Europe Recovery of Function Predictive Value of Tests Male Ventricular Function, Left Stroke Volume Middle Aged Time Factors Cardiac Resynchronization Therapy Devices Signal Processing, Computer-Assisted Heart Failure Cardiac Resynchronization Therapy Image Interpretation, Computer-Assisted Echocardiography, Doppler
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Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

Journal of neurointerventional surgery Nov 20, 2020
BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographi...
Self Expandable Metallic Stents Intracranial Aneurysm Balloon Occlusion Retrospective Studies Cohort Studies Humans Female Adult Male Middle Aged Treatment Outcome Follow-Up Studies Predictive Value of Tests Endovascular Procedures Machine Learning Algorithms Prospective Studies
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