Hospitalists

An Automated Deep Learning Method for Tile AO/OTA Pelvic Fracture Severity Grading from Trauma whole-Body CT.

Admission trauma whole-body CT is routinely employed as a first-line diagnostic tool for characterizing pelvic fracture severity. Tile AO/OTA grade based on the presence or absence of rotational and translational instability corresponds with need for interventions including massive transfusion and angioembolization. An automated method could be highly beneficial for point of care triage in this cr...

Added value of deep learning-based liver parenchymal CT volumetry for predicting major arterial injury after blunt hepatic trauma: a decision tree analysis.

PURPOSE: In patients presenting with blunt hepatic injury (BHI), the utility of CT for triage to hepatic angiography remains uncertain since simple binary assessment of contrast extravasation (CE) as being present or absent has only modest accuracy for major arterial injury on digital subtraction angiography (DSA). American Association for the Surgery of Trauma (AAST) liver injury grading is coars...

Hard for humans, hard for machines: predicting readmission after psychiatric hospitalization using narrative notes.

Machine learning has been suggested as a means of identifying individuals at greatest risk for hospital readmission, including psychiatric readmission...

Response to: Williams, Kotamarti, and Schulman re: "Outpatient Robot-Assisted Radical Prostatectomy: Are Patients Ready for Same-Day Discharge?" by Dobbs et al.

Image registration: Maximum likelihood, minimum entropy and deep learning.

In this work, we propose a theoretical framework based on maximum profile likelihood for pairwise and groupwise registration. By an asymptotic analysi...

Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.

To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinica...

Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda.

Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of ...

A Data-Driven Approach to Predict and Classify Epileptic Seizures from Brain-Wide Calcium Imaging Video Data.

The prediction of epileptic seizures has been an essential problem of epilepsy study. The calcium imaging video data images the whole brain-wide neuro...

Predicting the need for intubation in the first 24 h after critical care admission using machine learning approaches.

Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late ...

Using machine learning tools to predict outcomes for emergency department intensive care unit patients.

The number of critically ill patients has increased globally along with the rise in emergency visits. Mortality prediction for critical patients is vi...

Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). However, this operation is complex, and the peri-oper...

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray.

Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of art...

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) pr...

Pelvic Anatomical Features After Retzius-Sparing Robot-Assisted Radical Prostatectomy Intended for Early Recovery of Urinary Symptoms.

To elucidate factors contributing to early urinary continence recovery after retzius-sparing robot-assisted radical prostatectomy (RS-RARP) by evalua...

An Efficient Deep Learning Based Method for Speech Assessment of Mandarin-Speaking Aphasic Patients.

Speech assessment is an important part of the rehabilitation process for patients with aphasia (PWA). Mandarin speech lucidity features such as articu...

Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.

BACKGROUND: This study develops machine learning (ML) algorithms that use preoperative-only features to predict discharge-to-nonhome-facility (DNHF) a...

Iterative classifier optimizer-based pace regression and random forest hybrid models for suspended sediment load prediction.

Suspended sediment load is a substantial portion of the total sediment load in rivers and plays a vital role in determination of the service life of t...

Robot-Assisted Radical Cystectomy for Nonmetastatic Urothelial Carcinoma of Urinary Bladder: A Comparison Between Intracorporeal Versus Extracorporeal Orthotopic Ileal Neobladder.

To compare surgical, oncologic, functional outcomes and complication rate between intracorporeal neobladder (ICNB) and extracorporeal neobladder (ECN...

Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing.

BACKGROUND: Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and...

Adoption of Single-Port Robotic Prostatectomy: Two Alternative Strategies.

To demonstrate two distinct methods for adopting the single-port (SP) robotic surgery system for robotic-assisted laparoscopic prostatectomy (RALP) b...