Information Technology

A Biomedical Approach Via Telemedicine in the Treatment of a Child With Sensory Processing Disorder Using Diet and High-dose Biotin Intervention: A Case Report.

BACKGROUND: We present the case of a 6-y-old boy who was diagnosed with sensory processing disorder with developmental language and learning delay. He was treated successfully with diet and high-dose biotin along with other nutrient support that resulted in resolution of abnormal sensory behaviors and improvement in language and learning.

Early Prediction of Sepsis in EMR Records Using Traditional ML Techniques and Deep Learning LSTM Networks.

Sepsis is a life-threatening condition caused by infection and subsequent overreaction by the immune system. Physicians effectively treat sepsis with early administration of antibiotics. However, excessive use of antibiotics on false positive cases cultivates antibiotic resistant bacterial strains and can waste resources while false negative cases result in unacceptable mortality rates. Accurate e...

Improving Young Stroke Prediction by Learning with Active Data Augmenter in a Large-Scale Electronic Medical Claims Database.

Electronic medical claims (EMC) database has been successfully used for predicting occurrences of stroke and a variety of other diseases. However, ina...

Collaborative and Reproducible Research: Goals, Challenges, and Strategies.

Combining imaging biomarkers with genomic and clinical phenotype data is the foundation of precision medicine research efforts. Yet, biomedical imagin...

Using Natural Language Processing of Free-Text Radiology Reports to Identify Type 1 Modic Endplate Changes.

Electronic medical record (EMR) systems provide easy access to radiology reports and offer great potential to support quality improvement efforts and ...

Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment m...

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution.

Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are co...

Mapping Patient Trajectories using Longitudinal Extraction and Deep Learning in the MIMIC-III Critical Care Database.

Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and method...

Tobacco use status from clinical notes using Natural Language Processing and rule based algorithm.

BACKGROUND: This cross-sectional retrospective study utilized Natural Language Processing (NLP) to extract tobacco-use associated variables from clini...

Automatic Annotation of French Medical Narratives with SNOMED CT Concepts.

Medical data is multimodal. In particular, it is composed of both structured data and narrative data (free text). Narrative data is a type of unstruct...

FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability.

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitope...

Identification of errors in the IEDB using ontologies.

The Immune Epitope Database (IEDB) is a free online resource that has manually curated over 18 500 references from the scientific literature. Our data...

Structuring Clinical Decision Support Rules for Drug Safety Using Natural Language Processing.

Drug safety is an important aspect in healthcare, resulting in a number of inadvertent events, which may harm the patients. IT based Clinical Decision...

Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug events (ADEs) with pharmaceutical products. This article is...

Using Natural Language Processing to Extract Abnormal Results From Cancer Screening Reports.

OBJECTIVES: Numerous studies show that follow-up of abnormal cancer screening results, such as mammography and Papanicolaou (Pap) smears, is frequentl...

Finding useful data across multiple biomedical data repositories using DataMed.

The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the US Nat...

De-identification of patient notes with recurrent neural networks.

OBJECTIVE: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority o...

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electro...

Correlate: A PACS- and EHR-integrated Tool Leveraging Natural Language Processing to Provide Automated Clinical Follow-up.

A major challenge for radiologists is obtaining meaningful clinical follow-up information for even a small percentage of cases encountered and dictate...

PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneu...