Hospitalists

Deep-Learning-Based Automated Tracking and Counting of Living Plankton in Natural Aquatic Environments.

Plankton are widely distributed in the aquatic environment and serve as an indicator of water quality. Monitoring the spatiotemporal variation in plankton is an efficient approach to forewarning environmental risks. However, conventional microscopy counting is time-consuming and laborious, hindering the application of plankton statistics for environmental monitoring. In this work, an automated vid...

Supervised deep learning with vision transformer predicts delirium using limited lead EEG.

As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool. EEG is the criterion standard but is resource intensive thus not feasible for widespread delirium monitoring. This study evaluated the use of limited-lead rapid-response EEG and...

Random forest identifies predictors of discharge destination following total shoulder arthroplasty.

BACKGROUND: Machine learning algorithms are finding increasing use in prediction of surgical outcomes in orthopedics. Random forest is one of such alg...

Identifying Barriers to Post-Acute Care Referral and Characterizing Negative Patient Preferences Among Hospitalized Older Adults Using Natural Language Processing.

Our objective was to detect common barriers to post-acute care (B2PAC) among hospitalized older adults using natural language processing (NLP) of clin...

GPT-4: a new era of artificial intelligence in medicine.

GPT-4 is the latest version of ChatGPT which is reported by OpenAI to have greater problem-solving abilities and an even broader knowledge base. We ex...

Machine learning prediction of mortality in Acute Myocardial Infarction.

BACKGROUND: Acute Myocardial Infarction (AMI) is the leading cause of death in Portugal and globally. The present investigation created a model based ...

Reconstruction and analysis of negatively buoyant jets with interpretable machine learning.

In this paper, negatively inclined buoyant jets, which appear during the discharge of wastewater from processes such as desalination, are observed. A ...

Same-day discharge robot-assisted laparoscopic prostatectomy: feasibility, safety and patient experience.

OBJECTIVES: To report a single centre's experience of the feasibility, safety and patient acceptability of same-day discharge robot-assisted laparosco...

Self-Supervised Graph Learning With Hyperbolic Embedding for Temporal Health Event Prediction.

Electronic health records (EHRs) have been heavily used in modern healthcare systems for recording patients' admission information to health facilitie...

Automated prediction of COVID-19 severity upon admission by chest X-ray images and clinical metadata aiming at accuracy and explainability.

In the past few years COVID-19 posed a huge threat to healthcare systems around the world. One of the first waves of the pandemic hit Northern Italy s...

Clinical application of artificial intelligence algorithm for prediction of one-year mortality in heart failure patients.

Risk prediction for heart failure (HF) using machine learning methods (MLM) has not yet been established at practical application levels in clinical s...

Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: Performance assessment for the Great Barrier Reef marine park.

Continuous monitoring of oil discharges in coastal and open ocean waters using Earth Observation (EO) has undeniably contributed to diminishing their ...

Same day discharge for robot-assisted radical prostatectomy: a prospective cohort study documenting an Australian approach.

BACKGROUND: The introduction of robotic surgical systems has significantly impacted urological surgery, arguably more so than other surgical disciplin...

Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records.

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narrativ...

Quo Vadis, Amadeo Hand Robot? A Randomized Study with a Hand Recovery Predictive Model in Subacute Stroke.

BACKGROUND: Early identification of hand-prognosis-factors at patient's admission could help to select optimal synergistic rehabilitation programs bas...

Same-Day Discharge After Robot-Assisted Partial Nephrectomy: Is It Worth It?

Robot-assisted partial nephrectomy (RAPN) has traditionally been performed as an inpatient procedure; however, recent studies have suggested the feas...

Hourly Water Level Forecasting in an Hydroelectric Basin Using Spatial Interpolation and Artificial Intelligence.

In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were ...

Robot-assisted rehabilitation training improves knee function and daily activity ability in older adults following total knee arthroplasty.

To evaluate the effects of robot-assisted rehabilitation training on knee function and the daily activity ability of older adults following total knee...

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate ...

A Single-Institution Comparison of Robot-Assisted and Conventional Laparoscopic Colorectal Surgeries.

There has been ongoing discussion regarding the superiority of robotic laparoscopic surgery (RLS) over conventional laparoscopic surgery (CLS) in many...