Acta obstetricia et gynecologica Scandinavica
Mar 6, 2017
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.
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...
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...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
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...
BACKGROUND: Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung...
Clinical and experimental dermatology
Nov 25, 2025
BACKGROUND: In medical practice, clinic letters are essential for accurately documenting patient discussions, diagnoses and management plans. Traditionally, this involves a clinician dictating a summary after a consultation, which is transcribed by a...
BACKGROUND: Ensuring appropriate use of CT scans is critical for patient safety and resource optimization. Decision support tools and artificial intelligence (AI), such as large language models (LLMs), have the potential to improve CT referral justif...
Studies in health technology and informatics
Aug 7, 2025
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...
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