Medicare

AI-Assisted Processing Pipeline to Boost Protein Isoform Detection.

Proteomics, the study of proteins within biological systems, has seen remarkable advancements in recent years, with protein isoform detection emerging as one of the next major frontiers. One of the primary challenges is achieving the necessary peptide and protein coverage to confidently differentiate isoforms as a result of the protein inference problem and protein false discovery rate estimation ...

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reducing the risk of poor pregnancy outcomes. GDM is usually diagnosed and detected after 24 weeks of gestation, while complications due to GDM can occur m...

Hypomagnesemia and 25-hydroxyvitamin D deficiency in patients with long COVID.

Clinical manifestations related to hypomagnesemia and/or deficiency of vitamin D are frequent in patients with an extended course of coronavirus disea...

Unlocking glioma genetics with deep learning.

The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of human disease. CHARM, an AI algorithm described in t...

Use of artificial intelligence for cancer clinical trial enrollment: a systematic review and meta-analysis.

BACKGROUND: The aim of this study is to provide a comprehensive understanding of the current landscape of artificial intelligence (AI) for cancer clin...

Analysis of the influence of surgical robot drilling parameters on the temperature of skull drilling based on Box-Behnken design.

It is easy to cause thermal damage to the bone tissue when the surgical robot performs skull drilling to remove bone flaps, due to the large diameter ...

Contrastive learning of protein representations with graph neural networks for structural and functional annotations.

Although protein sequence data is growing at an ever-increasing rate, the protein universe is still sparsely annotated with functional and structural ...

[Fostering Pharmacists to Succeed in a Drastically Changing Society].

In 2006, Japan's pharmaceutical science education was revised to a 6-year enrollment course, placing greater emphasis on cultivating practical clinica...

DeepSCP: utilizing deep learning to boost single-cell proteome coverage.

Multiplexed single-cell proteomes (SCPs) quantification by mass spectrometry greatly improves the SCP coverage. However, it still suffers from a low n...

[Effect of electrode array type and insertion technique on the insertion force: in vitro cochlear model study].

To investigate the effect of insertion technique and electrode array type on the insertion force of electrode array, and to provide a basis for furth...

Increasing metadata coverage of SRA BioSample entries using deep learning-based named entity recognition.

High-quality metadata annotations for data hosted in large public repositories are essential for research reproducibility and for conducting fast, pow...

Key Principles of Clinical Validation, Device Approval, and Insurance Coverage Decisions of Artificial Intelligence.

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical valida...

Critical Review of Data Analytics Techniques used in the Expanded Program on Immunization (EPI).

BACKGROUND: Immunization is a significant public health intervention to reduce child mortality and morbidity. However, its coverage, in spite of free ...

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 allowabl...

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 treatmen...

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...