AIMC Topic: Tertiary Care Centers

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Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital.

Journal of translational medicine
BACKGROUND: Clinical risk scores and machine learning models based on routine laboratory values could assist in automated early identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients at risk for severe clinical outcom...

Comparison of Robot-Assisted and Laparoscopic Partial Nephrectomy for Renal Hilar Tumors: Results from a Tertiary Referral Center.

Journal of endourology
To compare perioperative, functional, and oncologic outcomes between robot-assisted partial nephrectomy (RAPN) and laparoscopic partial nephrectomy (LPN) for renal hilar tumors. We retrospectively reviewed patients who underwent minimally invasive ...

Extravalidation and reproducibility results of a commercial deep learning-based automatic detection algorithm for pulmonary nodules on chest radiographs at tertiary hospital.

Journal of medical imaging and radiation oncology
INTRODUCTION: To extra validate and evaluate the reproducibility of a commercial deep convolutional neural network (DCNN) algorithm for pulmonary nodules on chest radiographs (CRs) and to compare its performance with radiologists.

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...

Combined robotic approach and enhanced recovery after surgery pathway for optimization of costs in patients undergoing proctectomy.

BJS open
BACKGROUND: Enhanced recovery after surgery (ERAS) pathways are beneficial in proctocolectomy, but their impact on robotic low rectal proctectomy is not fully investigated. This study assessed the impact of an ERAS pathway on the outcomes and cost of...

Prediction of vaginal birth after cesarean deliveries using machine learning.

American journal of obstetrics and gynecology
BACKGROUND: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliver...

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

Scientific reports
In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (PTB) screening when interpreted by human readers. However, they are challenging to scale due to hardware costs and the dearth of pro...

Triaging ophthalmology outpatient referrals with machine learning: A pilot study.

Clinical & experimental ophthalmology
IMPORTANCE: Triaging of outpatient referrals to ophthalmology services is required for the maintenance of patient care and appropriate resource allocation. Machine learning (ML), in particular natural language processing, may be able to assist with t...

Molecular mechanisms of antibiotic co-resistance among carbapenem resistant Acinetobacter baumannii.

Journal of infection in developing countries
INTRODUCTION: The spread of carbapenem-resistant Acinetobacter baumannii (CRAB) is difficult to control especially in the hospitals due to the successful mobilization and evolution of the genetic elements harboring the resistant determinants. The stu...

Validation of an alcohol misuse classifier in hospitalized patients.

Alcohol (Fayetteville, N.Y.)
BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health reco...