AIMC Topic: Algorithms

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Accelerometer-Based Fall Detection Using Machine Learning: Training and Testing on Real-World Falls.

Sensors (Basel, Switzerland)
Falling is a significant health problem. Fall detection, to alert for medical attention, has been gaining increasing attention. Still, most of the existing studies use falls simulated in a laboratory environment to test the obtained performance. We a...

Diagnosis of thyroid neoplasm using support vector machine algorithms based on platelet RNA-seq.

Endocrine
OBJECTIVE: To assess the capacity of support vector machine (SVM) algorithms that are developed based on platelet RNA-seq data in identifying thyroid neoplasm patients and differentiating patients with thyroid adenomas, papillary thyroid cancer and m...

A Decision Tree-Initialised Neuro-fuzzy Approach for Clinical Decision Support.

Artificial intelligence in medicine
Apart from the need for superior accuracy, healthcare applications of intelligent systems also demand the deployment of interpretable machine learning models which allow clinicians to interrogate and validate extracted medical knowledge. Fuzzy rule-b...

A real-time system using deep learning to detect and track ureteral orifices during urinary endoscopy.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: To automatically identify and locate various types and states of the ureteral orifice (UO) in real endoscopy scenarios, we developed and verified a real-time computer-aided UO detection and tracking system using an improved ...

Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization.

Journal of chemical information and modeling
The three-dimensional structures and shapes of biomolecules provide essential information about their interactions and functions. Unfortunately, the computational cost of biomolecular shape representation is an active challenge which increases rapidl...

Identification of Heart Sounds with an Interpretable Evolving Fuzzy Neural Network.

Sensors (Basel, Switzerland)
Heart problems are responsible for the majority of deaths worldwide. The use of intelligent techniques to assist in the identification of existing patterns in these diseases can facilitate treatments and decision making in the field of medicine. This...

Machine Learning Methods in Drug Discovery.

Molecules (Basel, Switzerland)
The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been use...

Developing an Individual Glucose Prediction Model Using Recurrent Neural Network.

Sensors (Basel, Switzerland)
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of...

An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.

Sensors (Basel, Switzerland)
In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG...

Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images.

Scientific reports
A brain tumor is an uncontrolled growth of cancerous cells in the brain. Accurate segmentation and classification of tumors are critical for subsequent prognosis and treatment planning. This work proposes context aware deep learning for brain tumor s...