AIMC Topic: Referral and Consultation

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Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer.

Artificial intelligence in medicine
OBJECTIVE: Machine learning techniques can be used to extract predictive models for diseases from electronic medical records (EMRs). However, the nature of EMRs makes it difficult to apply off-the-shelf machine learning techniques while still exploit...

Predicting Health Care Utilization After Behavioral Health Referral Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Mental health problems are an independent predictor of increased healthcare utilization. We created random forest classifiers for predicting two outcomes following a patient's first behavioral health encounter: decreased utilization by any amount (AU...

Machine-Learning-Based Prediction of Suicide Risk Using Preliminary Questionnaire and Consultation Text.

Studies in health technology and informatics
In Japan, chat-based mental health counseling services have low response rates due to understaffing. In this article, machine learning (ML) based suicide risk classification methods are proposed. A dataset was constructed including a medical question...

Patterns in GP appointment systems: a cluster analysis of 3480 English practices.

The British journal of general practice : the journal of the Royal College of General Practitioners
BACKGROUND: In response to increasing demand for appointments, UK general practices have adopted a range of appointment systems. These systems vary widely in implementation. These changes have not yet been clearly described.

Comparative analysis of clinical relevance and accuracy in AI-assisted patient consultations on ankle and clavicle fracture surgeries.

Injury
BACKGROUND: It is becoming increasingly important to evaluate the effectiveness of large language models (LLMs) and query-assisted platforms like Google and ChatGPT in providing clinically relevant and accurate information to patient-initiated inquir...

Machine Learning and Deep Learning Models for Automated Protocoling of Emergency Brain MRI Using Text from Clinical Referrals.

Radiology. Artificial intelligence
Purpose To develop and evaluate machine learning and deep learning-based models for automated protocoling of emergency brain MRI scans based on clinical referral text. Materials and Methods In this single-institution, retrospective study of 1953 emer...

Reducing diagnostic delays in acute hepatic porphyria using health records data and machine learning.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of 15 years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recogn...