Medicare

Patient Coded Severity and Payment Penalties Under the Hospital Readmissions Reduction Program: A Machine Learning Approach.

OBJECTIVE: The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowable secondary diagnoses in January 2011 and its association with financial penalties under the Hospital Readmission Reduction Program (HRRP).

Machine Learning Classifier Models Can Identify Acute Respiratory Distress Syndrome Phenotypes Using Readily Available Clinical Data.

Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with differential clinical outcomes and responses to randomly assigned treatment have consistently been identified in randomized controlled trial cohorts using latent class analysis. Plasma biomarkers, key components in phenotype identification, currently lack point-of-care assays and represent a barrier to the clinical impleme...

Assessing the enrichment of dietary supplement coverage in the Unified Medical Language System.

OBJECTIVE: We sought to assess the need for additional coverage of dietary supplements (DS) in the Unified Medical Language System (UMLS) by investiga...

Machine intelligence for early targeted precision management and response to outbreaks of respiratory infections.

OBJECTIVES: To evaluate the utility of machine learning (ML) for the management of Medicare beneficiaries at risk of severe respiratory infections in ...

Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants wer...

Using Machine Learning to Predict Primary Care and Advance Workforce Research.

PURPOSE: To develop and test a machine-learning-based model to predict primary care and other specialties using Medicare claims data.

Commercial Adoption of AI in the Healthcare Sector: An Exploratory Analysis of S&P500 Companies.

The use of Artificial Intelligence (AI) technologies within the healthcare sector is growing. However, there are differences in the speed of commercia...

Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle.

Genetic control methods of mosquito vectors of malaria, dengue, yellow fever, and Zika are becoming increasingly popular due to the limitations of oth...

Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care.

Big data for health care is one of the potential solutions to deal with the numerous challenges of health care, such as rising cost, aging population,...

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

BACKGROUND: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease ...

Does machine learning improve prediction of VA primary care reliance?

OBJECTIVES: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are du...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories about teens whose death from suicide was attributed t...

Data-driven method to enhance craniofacial and oral phenotype vocabularies.

BACKGROUND: A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clini...

Radiology-Pathology Correlation to Facilitate Peer Learning: An Overview Including Recent Artificial Intelligence Methods.

Correlation of pathology reports with radiology examinations has long been of interest to radiologists and helps to facilitate peer learning. Such cor...

Obtaining Knowledge in Pathology Reports Through a Natural Language Processing Approach With Classification, Named-Entity Recognition, and Relation-Extraction Heuristics.

PURPOSE: Robust institutional tumor banks depend on continuous sample curation or else subsequent biopsy or resection specimens are overlooked after i...

Monitoring of Patient Blanket Coverage using 3D Camera Data.

Nurses in a hospital are responsible for the monitoring and care of a large number of patients. Regularly checking if patients are sufficiently covere...

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.

Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learning technique called Bayesian Additive Regression Tr...

Machine Learning Algorithm Helps Identify Non-Diagnosed Prodromal Alzheimer's Disease Patients in the General Population.

BACKGROUND: Recruiting patients for clinical trials of potential therapies for Alzheimer's disease (AD) remains a major challenge, with demand for tri...

Hercules: a profile HMM-based hybrid error correction algorithm for long reads.

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several types of stud...

Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions.

A diverse universe of statistical models in the literature aim to help hospitals understand the risk factors of their preventable readmissions. Howeve...