AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Analysis of Decision Tree and K-Nearest Neighbor Algorithm in the Classification of Breast Cancer.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: The death rate of breast tumour is falling as there is progress in its research area. However, it is the most common disease among women. It is a great challenge in designing a machine learning model to evaluate the performance of the clas...

Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Chemosphere
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the predi...

Towards near real-time assessment of surgical skills: A comparison of feature extraction techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable a...

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction.

Journal of biophotonics
The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance...

3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods.

PloS one
Boosting is a family of supervised learning algorithm that convert a set of weak learners into a single strong one. It is popular in the field of object tracking, where its main purpose is to extract the position, motion, and trajectory from various ...

The assessment of efficient representation of drug features using deep learning for drug repositioning.

BMC bioinformatics
BACKGROUND: De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly used in cases with a limited num...

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...

Input representations and classification strategies for automated human gait analysis.

Gait & posture
BACKGROUND: Quantitative gait analysis produces a vast amount of data, which can be difficult to analyze. Automated gait classification based on machine learning techniques bear the potential to support clinicians in comprehending these complex data....

Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.

PloS one
OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.