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A Hybrid Model for 30-Day Syncope Prognosis Prediction in the Emergency Department.

Syncope is a challenging problem in the emergency department (ED) as the available risk prediction t...

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore.

Protein post-translational modifications (PTMs) play a crucial role in countless biological processe...

Early-stage neutralizing antibody level associated with the re-positive risk of Omicron SARS-CoV-2 RNA in patients recovered from COVID-19.

Post-discharge re-positivity of Omicron SARS-CoV-2 is challenging for the sufficient control of this...

EFFICIENT ESTIMATION OF THE MAXIMAL ASSOCIATION BETWEEN MULTIPLE PREDICTORS AND A SURVIVAL OUTCOME.

This paper develops a new approach to post-selection inference for screening high-dimensional predic...

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their abilit...

Deep learning-based whole-body characterization of prostate cancer lesions on [Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence.

PURPOSE: The automatic segmentation and detection of prostate cancer (PC) lesions throughout the bod...

Assessment of Preoperative Risk Factors for Post-LASIK Ectasia Development.

PURPOSE: To evaluate preoperative risk factors (mainly those related to corneal topography/tomograph...

Spirometry services in England post-pandemic and the potential role of AI support software: a qualitative study of challenges and opportunities.

BACKGROUND: Spirometry services to diagnose and monitor lung disease in primary care were identified...

Enhancing diagnosis of Hirschsprung's disease using deep learning from histological sections of post pull-through specimens: preliminary results.

PURPOSE: Accurate histological diagnosis in Hirschsprung disease (HD) is challenging, due to its com...

Machine-learning assisted swallowing assessment: a deep learning-based quality improvement tool to screen for post-stroke dysphagia.

INTRODUCTION: Post-stroke dysphagia is common and associated with significant morbidity and mortalit...

Machine learning algorithms for the prognostication of abdominal aortic aneurysm progression: a systematic review.

INTRODUCTION: Abdominal aortic aneurysm (AAA), often characterized by an abdominal aortic diameter o...

A transformer-based deep learning approach for fairly predicting post-liver transplant risk factors.

Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There ar...

Application of natural language processing to post-structuring of rectal cancer MRI reports.

AIM: To evaluate a natural language processing (NLP) system for extracting structured information fr...

Robotic retroperitoneal lymph node dissection for paratesticular rhabdomyosarcoma in adolescents: a case series.

Robotic assisted (RA) retroperitoneal lymph node dissection (RPLND) has grown in popularity as it of...

Artificial intelligence and machine learning for clinical pharmacology.

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug disco...

Revolutionizing Peptide-Based Drug Discovery: Advances in the Post-AlphaFold Era.

Peptide-based drugs offer high specificity, potency, and selectivity. However, their inherent flexib...

Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance.

INTRODUCTION: As part of routine safety surveillance, thousands of articles of potential interest ar...

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