AIMC Topic: Algorithms

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Predicting mutant outcome by combining deep mutational scanning and machine learning.

Proteins
Deep mutational scanning provides unprecedented wealth of quantitative data regarding the functional outcome of mutations in proteins. A single experiment may measure properties (eg, structural stability) of numerous protein variants. Leveraging the ...

Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database.

Biomechanics and modeling in mechanobiology
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...

A semi-supervised autoencoder framework for joint generation and classification of breathing.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the sufficient number of samples needed for diagnostic and treatment purpose...

Securing Bio-Cyber Interface for the Internet of Bio-Nano Things using Particle Swarm Optimization and Artificial Neural Networks based parameter profiling.

Computers in biology and medicine
Internet of bio-nano things (IoBNT) is a novel communication paradigm where tiny, biocompatible and non-intrusive devices collect and sense biological signals from the environment and send them to data centers for processing through the internet. The...

Privacy preserving distributed learning classifiers - Sequential learning with small sets of data.

Computers in biology and medicine
BACKGROUND: Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this study we investigated the...

Implementation of a Deep Learning Algorithm Based on Vertical Ground Reaction Force Time-Frequency Features for the Detection and Severity Classification of Parkinson's Disease.

Sensors (Basel, Switzerland)
Conventional approaches to diagnosing Parkinson's disease (PD) and rating its severity level are based on medical specialists' clinical assessment of symptoms, which are subjective and can be inaccurate. These techniques are not very reliable, partic...

Explainable Anomaly Detection Framework for Maritime Main Engine Sensor Data.

Sensors (Basel, Switzerland)
In this study, we proposed a data-driven approach to the condition monitoring of the marine engine. Although several unsupervised methods in the maritime industry have existed, the common limitation was the interpretation of the anomaly; they do not ...

Machine learning in medicine: a practical introduction to natural language processing.

BMC medical research methodology
BACKGROUND: Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of wri...

Intelligent Disease Prediagnosis Only Based on Symptoms.

Journal of healthcare engineering
People often concern the relationships between symptoms and diseases when seeking medical advices. In this paper, medical data are divided into three copies, records related to main disease categories, records related to subclass disease types, and r...