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Referral and Consultation

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Text Mining and Automation for Processing of Patient Referrals.

Applied clinical informatics
BACKGROUND: Various tasks within health care processes are repetitive and time-consuming, requiring personnel who could be better utilized elsewhere. The task of assigning clinical urgency categories to internal patient referrals is one such case of ...

Evaluation of three machine learning models for self-referral decision support on low back pain in primary care.

International journal of medical informatics
BACKGROUND: Most people experience low back pain (LBP) at least once in their life and for some patients this evolves into a chronic condition. One way to prevent acute LBP from transiting into chronic LBP, is to ensure that patients receive the righ...

Introduction of robot-assisted radical hysterectomy for early stage cervical cancer: impact on complications, costs and oncologic outcome.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: The objective was to assess the impact of robot-assisted radical hysterectomy (RRH) on surgical and oncologic outcome and costs compared with open radical hysterectomy (ORH) at a tertiary referral center in Sweden.

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer.

PloS one
Individuals with colorectal cancer (CRC) have a tendency to intestinal bleeding which may result in mild to severe iron deficiency anemia, but for many colon cancer patients hematological abnormalities are subtle. The fecal occult blood test (FOBT) i...

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 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...