AIMC Topic: Machine Learning

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Powerlifting score prediction using a machine learning method.

Mathematical biosciences and engineering : MBE
This research discusses an interesting topic, using artificial intelligence methods to predict the score of powerlifters. We collected the characteristics of powerlifters, and then used the reservoir computing extreme learning machine to build a pred...

[Random survival forest: applying machine learning algorithm in survival analysis of biomedical data].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this incon...

Drivers of Prolonged Hospitalization Following Spine Surgery: A Game-Theory-Based Approach to Explaining Machine Learning Models.

The Journal of bone and joint surgery. American volume
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...

Artificial intelligence in cancer diagnostics and therapy: current perspectives.

Indian journal of cancer
Artificial intelligence (AI) has found its way into every sphere of human life including the field of medicine. Detection of cancer might be AI's most altruistic and convoluted challenge to date in the field of medicine. Embedding AI into various asp...

Gene Classification Based on Multi-Class SVMs with Systematic Sampling and Hierarchical Clustering (SSHC) Algorithm.

Advances in experimental medicine and biology
The support vector machines (SVMs) is one of the machine learning algorithms with high classification accuracy. However, the support vector machine algorithm has a very high training complexity. Thus, it is not very efficient with large datasets. In ...

Development of a Diagnostic Tool for Balance Disorders Based on Machine Learning Techniques.

Advances in experimental medicine and biology
A diagnostic tool is developed for balance disorders based on machine learning techniques. This tool is addressed at experts, in order to support the diagnosis of 5 categories of balance disorders and ultimately 11 specific disorders. Unlike previous...

Web-Based Decision Support System for Coronary Heart Disease Diagnosis.

Advances in experimental medicine and biology
Coronary heart disease is a serious and common disease that affects a large part of the population. There is a tendency to use machine learning techniques for the punctual and valid diagnosis, which can determine the effectiveness of treatment and th...

Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.

Cancer control : journal of the Moffitt Cancer Center
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classifie...

Colorectal Cancer Detected by Machine Learning Models Using Conventional Laboratory Test Data.

Technology in cancer research & treatment
Current diagnostic methods for colorectal cancer (CRC) are colonoscopy and sigmoidoscopy, which are invasive and complex procedures with possible complications. This study aimed to determine models for CRC identification that involve minimally invas...