AIMC Topic: Female

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Fast and automatic assessment of fall risk by coupling machine learning algorithms with a depth camera to monitor simple balance tasks.

Journal of neuroengineering and rehabilitation
BACKGROUND: Falls in the elderly constitute a major health issue associated to population ageing. Current clinical tests evaluating fall risk mostly consist in assessing balance abilities. The devices used for these tests can be expensive or inconven...

Discriminant analysis and machine learning approach for evaluating and improving the performance of immunohistochemical algorithms for COO classification of DLBCL.

Journal of translational medicine
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL clas...

Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance.

Computational and mathematical methods in medicine
Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB). Significant gaps remain in our understanding on how to predict HBsAg seroclearance accurately and ...

Comparative outcomes of minimally invasive and robotic-assisted esophagectomy.

Surgical endoscopy
OBJECTIVE: Minimally invasive esophagectomy (MIE) has demonstrated superior outcomes compared to open approaches. The myriad of techniques has precluded the recommendation of a standard approach. The addition of robotics to esophageal resection has p...

Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

Archives of suicide research : official journal of the International Academy for Suicide Research
This study applies classification tree analysis to prospectively identify suicide attempters among a large adolescent community sample, to demonstrate the strengths and limitations of this approach for risk identification. Data were drawn from the Na...

Artificial neural network optimizes self-examination of osteoporosis risk in women.

The Journal of international medical research
OBJECTIVE: This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool for Asians (OSTA) score.

Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

Journal of medical Internet research
BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, which can potentially reduce the escalat...

A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features.

BMC bioinformatics
BACKGROUND: It is of great clinical significance to develop an accurate computer aided system to accurately diagnose the breast cancer. In this study, an enhanced machine learning framework is established to diagnose the breast cancer. The core of th...

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use could improve risk stratification, shared decision-making, and patient counseling before surgery.