AIMC Topic:
New York

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Predicting hospital length of stay using machine learning on a large open health dataset.

BMC health services research
BACKGROUND: Governments worldwide are facing growing pressure to increase transparency, as citizens demand greater insight into decision-making processes and public spending. An example is the release of open healthcare data to researchers, as health...

An assessment of perioperative outcomes for open, laparoscopic, and robot-assisted pancreaticoduodenectomy in New York State.

Journal of surgical oncology
BACKGROUND: Minimally invasive techniques for pancreaticoduodenectomy (PD) are increasing in practice, however, data remains limited regarding perioperative outcomes. Our study sought to compare patients undergoing open pancreaticoduodenectomy (OPD) ...

Outcomes following robot-assisted versus laparoscopic sleeve gastrectomy: the New York State experience.

Surgical endoscopy
INTRODUCTION: Laparoscopic sleeve gastrectomy (LSG) represents more than half of all bariatric procedures in the USA, and robot-assisted sleeve gastrectomy (RSG) is becoming increasingly common. There is a paucity of evidence regarding postoperative ...

The use of a next-generation sequencing-derived machine-learning risk-prediction model (OncoCast-MPM) for malignant pleural mesothelioma: a retrospective study.

The Lancet. Digital health
BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on disease stage and histology is inadequate. For some individuals with early-stage epithelioid tumours, a good prognosis by current guidelines can progres...

Robotic Prostatectomy and Prostate Cancer-Related Medicaid Spending: Evidence from New York State.

Journal of general internal medicine
BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes in treatment patterns. The net effect of this technology on Medicaid spending has not been assessed.

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

International journal of medical sciences
This study aimed to develop a machine learning algorithm to identify key clinical measures to triage patients more effectively to general admission versus intensive care unit (ICU) admission and to predict mortality in COVID-19 pandemic. This retro...

Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.

The Annals of thoracic surgery
BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many lives, but it is associated with a high degree of patient morbidity, mortality, and resource use. This study aimed to develop a machine learning algorithm...

Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This d...

Prediction of microbial communities for urban metagenomics using neural network approach.

Human genomics
BACKGROUND: Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious dise...