Medicare

Validation of Codes to Distinguish Between Claudication and Chronic Limb-Threatening Ischemia in Patients Undergoing Peripheral Vascular Intervention Using Medicare-Matched Registry Data.

BACKGROUND: The accuracy of contemporary administrative claims codes to discriminate between different phenotypes of peripheral artery disease is not well defined. We aimed to validate a predefined set of , codes used to distinguish between claudication and chronic limb-threatening ischemia (CLTI) and to optimize their diagnostic accuracy using a supervised machine-learning approach.

Incorporating organ deformation in biological modeling and patient outcome study for permanent prostate brachytherapy.

Permanent prostate brachytherapy has inherent intraoperative organ deformation due to the inflatable trans-rectal ultrasound probe cover. Since the majority of the dose is delivered postoperatively with no deformation, the dosimetry approved at the time of implant may not accurately represent the dose delivered to the target and organs at risk. We aimed to evaluate the biological effect of the pro...

Electroencephalography microstates predict 12-h abstinence-induced craving changes in young smokers.

Nicotine abstinence inhibits the function of the mesolimbic dopamine system to enhance craving. EEG microstates may provide spatiotemporal characteris...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 2. COMI item-content, scoring, language versions, and applications.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 1. Development of the COMI, interpretation of scores, and use in research.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

Enhancing biomarker based oncology trial matching using large language models.

Clinical trials are an essential component of drug development for new cancer treatments, yet the information required to determine a patient's eligib...

Improving Foundation Model for Endoscopy Video Analysis via Representation Learning on Long Sequences.

Recent advancements in endoscopy video analysis have relied on the utilization of relatively short video clips extracted from longer videos or million...

Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic ...

A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.

The accurate prediction of RNA secondary structure, and pseudoknots in particular, is of great importance in understanding the functions of RNAs since...

Deep Learning-Based Prediction of Decoy Spectra for False Discovery Rate Estimation in Spectral Library Searching.

With the advantage of extensive coverage, predicted spectral libraries are becoming an attractive alternative in proteomic data analysis. As a popular...

Assessing the Usability of ChatGPT Responses Compared to Other Online Information in Hand Surgery.

BACKGROUND: ChatGPT is a natural language processing tool with potential to increase accessibility of health information. This study aimed to: (1) ass...

Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.

This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST...

Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.

Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated...

An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.

PURPOSE: Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (P...

Opportunities and Challenges for Large Language Models in Primary Health Care.

Primary Health Care (PHC) is the cornerstone of the global health care system and the primary objective for achieving universal health coverage. China...

ZnO nanoflower-mediated paper-based electrochemical biosensor for perfect classification of cardiac biomarkers with physics-informed machine learning.

The widespread exposure of acute myocardial infarction globally demands an ultrasensitive, rapid, and cost-effective biosensor for troponin-I and T in...

Student dropout prediction through machine learning optimization: insights from moodle log data.

Student attrition and academic failure remain pervasive challenges in education, often occurring at substantial rates and posing considerable difficul...

SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants.

Structural variations (SVs) are diverse forms of genetic alterations and drive a wide range of human diseases. Accurately genotyping SVs, particularly...

Enhancement of long-horizon task planning via active and passive modification in large language models.

This study proposes a method for generating complex and long-horizon off-line task plans using large language models (LLMs). Although several studies ...

Association of High-Deductible Health Plans and Complicated Appendicitis Among Children.

OBJECTIVE: To determine whether high-deductible health plans (HDHPs) are associated with complicated disease and hospitalization costs for children wi...