Operating Room Usage Time Estimation with Machine Learning Models.

Effectively handling the limited number of surgery operating rooms equipped with expensive equipment is a challenging task for hospital management such as reducing the case-time duration and reducing idle time. Improving the efficiency of operating room usage via reducing the idle time with better scheduling would rely on accurate estimation of surgery duration. Our model can achieve a good prediction result on surgery duration with a dozen of features.

Breast cancer recurrence prediction with ensemble methods and cost-sensitive learning.

Breast cancer is one of the most common cancers in women all over the world. Due to the improvement of medical treatments, most of the breast cancer patients would be in remission. However, the patients have to face the next challenge, the recurrence of breast cancer which may cause more severe effects, and even death.

Digitizing abdominal palpation with a pressure measurement and positioning device.

An abdominal physical examination is one of the most important tools in evaluating patients with acute abdominal pain. We focused on palpation, in which assessment is made according to the patient's response and force feedback. Since palpation is performed manually by the examiner, the uniformity of force and location is difficult to achieve during examinations.

Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records.

The International Statistical Classification of Disease and Related Health Problems (ICD) is an international standard system for categorizing and reporting diseases, injuries, disorders, and health conditions. Most previously-proposed disease predicting systems need clinical information collected by the medical staff from the patients in hospitals. In this paper, we propose a deep learning algorithm to classify disease types and identify diagnostic codes by using only the subjective component of progress notes in medical records.

Serum Glutamine Levels as a Potential Diagnostic Biomarker in Sepsis following Surgery for Peritonitis.

Few diagnostic biomarkers for sepsis after emergency peritonitis surgery are available to clinicians, and, thus, it is important to develop new biomarkers for patients undergoing this procedure. We investigated whether serum glutamine and selenium levels could be diagnostic biomarkers of sepsis in individuals recovering from emergency peritonitis surgery. From February 2012 to March 2013, patients who had peritonitis diagnosed at the emergency department and underwent emergency surgery were screened for eligibility.

Viral warts (Human Papilloma Virus) as a potential risk for breast cancer among younger females.

Introduction: There have been several reports on the role of human papillomavirus (HPV) in the etiology of breast cancer. To our knowledge, this is first study to use disease-disease association data-mining approach to analyzing viral warts and breast cancer to be conducted in Taiwanese population.

Materials And Methods: We analyzed the Taiwan's National Health Insurance database (NHIDM data comprising of 23 million patient data) to examine the association between viral warts and female breast carcinoma.

Applying under-sampling techniques and cost-sensitive learning methods on risk assessment of breast cancer.

Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources.

Novel solutions for an old disease: diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks.

Background: Diagnosing acute appendicitis clinically is still difficult. We developed random forests, support vector machines, and artificial neural network models to diagnose acute appendicitis.

Methods: Between January 2006 and December 2008, patients who had a consultation session with surgeons for suspected acute appendicitis were enrolled.