AIMC Topic: Electronic Health Records

Clear Filters Showing 2191 to 2200 of 2670 articles

Comparative analysis of weka-based classification algorithms on medical diagnosis datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: With the advent of 5G and the era of Big Data, the rapid development of medical information technology around the world, the massive application of electronic medical records and cases, and the digitization of medical equipment and instru...

Prescreening in oncology trials using medical records. Natural language processing applied on lung cancer multidisciplinary team meeting reports.

Health informatics journal
Defining profiles of patients that could benefit from relevant anti-cancer treatments is essential. An increasing number of specific criteria are necessary to be eligible to specific anti-cancer therapies. This study aimed to develop an automated alg...

Cost supervision mining from EMR based on artificial intelligence technology.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: To effectively monitor medical insurance funds in the era of big data, the study tries to construct an inpatient cost rationality judgement model by designing a virtuous cycle of inpatient cost supervision information system and exploring...

Management Opportunities and Challenges After Achieving Widespread Health System Digitization.

Advances in health care management
The adoption of electronic health records (EHRs) and digitization of health data over the past decade is ushering in the next generation of digital health tools that leverage artificial intelligence (AI) to improve varied aspects of health system per...

Artificial intelligence for multimodal data integration in oncology.

Cancer cell
In oncology, the patient state is characterized by a whole spectrum of modalities, ranging from radiology, histology, and genomics to electronic health records. Current artificial intelligence (AI) models operate mainly in the realm of a single modal...

A Framework for Automating Psychiatric Distress Screening in Ophthalmology Clinics Using an EHR-Derived AI Algorithm.

Translational vision science & technology
PURPOSE: In patients with ophthalmic disorders, psychosocial risk factors play an important role in morbidity and mortality. Proper and early psychiatric screening can result in prompt intervention and mitigate its impact. Because screening is resour...

Development and Validation of a Machine Learning Approach Leveraging Real-World Clinical Narratives as a Predictor of Survival in Advanced Cancer.

JCO clinical cancer informatics
PURPOSE: Predicting short-term mortality in patients with advanced cancer remains challenging. Whether digitalized clinical text can be used to build models to enhance survival prediction in this population is unclear.

Identification of Patients With Metastatic Prostate Cancer With Natural Language Processing and Machine Learning.

JCO clinical cancer informatics
PURPOSE: Understanding treatment patterns and effectiveness for patients with metastatic prostate cancer (mPCa) is dependent on accurate assessment of metastatic status. The objective was to develop a natural language processing (NLP) model for ident...

A scoping review of publicly available language tasks in clinical natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To provide a scoping review of papers on clinical natural language processing (NLP) shared tasks that use publicly available electronic health record data from a cohort of patients.

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support.

Journal of the American Medical Informatics Association : JAMIA
Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in th...