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Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids.
Clinical therapeutics
Mar 29, 2021
PURPOSE: Coronavirus disease-2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guidelines have supported the use of corticosteroids or remdesivir in the treatment of COVID-19. However...
Reperfusion Therapy in Acute Ischemic Stroke with Active Cancer: A Meta-Analysis Aided by Machine Learning.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 26, 2021
OBJECTIVES: While the prevalence of active cancer patients experiencing acute stroke is increasing, the effects of active cancer on reperfusion therapy outcomes are inconclusive. Thus, we aimed to compare the safety and outcomes of reperfusion therap...
Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.
The Lancet. Digital health
Mar 24, 2021
BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with COVID-19. We aimed to develop and evaluate an artificial intelligence system using chest x-rays and ...
Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.
BMC pulmonary medicine
Mar 24, 2021
BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretati...
Assessing Rectal Cancer Treatment Response Using Coregistered Endorectal Photoacoustic and US Imaging Paired with Deep Learning.
Radiology
Mar 23, 2021
Background Conventional radiologic modalities perform poorly in the radiated rectum and are often unable to differentiate residual cancer from treatment scarring. Purpose To report the development and initial patient study of an imaging system compri...
Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI.
Human brain mapping
Mar 18, 2021
Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as those afflicted with Parkinson's disease (PD), dystonia, and essential tremor (ET), by relieving mot...
Accurate prediction of acute pancreatitis severity with integrative blood molecular measurements.
Aging
Mar 10, 2021
BACKGROUND: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results fo...
A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis.
BMC cancer
Mar 10, 2021
BACKGROUND: Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spectra of small, surgically obtained tissue samples, and is a promising novel diagnostic tool when combined with machine learning which discriminates ma...
Novel "Modified Bascule Method" for Lymphadenectomy Along the Left Recurrent Laryngeal Nerve During Robot-Assisted Minimally Invasive Esophagectomy.
Annals of surgical oncology
Mar 8, 2021
BACKGROUND: Given the worldwide popularization of conventional minimally invasive esophagectomy (C-MIE), robot-assisted MIE (RAMIE) can be expected to provide a finer procedure. However, controversy remains regarding whether RAMIE is superior to C-MI...
Cardiac Operative Risk in Latin America: A Comparison of Machine Learning Models vs EuroSCORE-II.
The Annals of thoracic surgery
Mar 6, 2021
BACKGROUND: Machine learning is a useful tool for predicting medical outcomes. This study aimed to develop a machine learning-based preoperative score to predict cardiac surgical operative mortality.
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