AIMC Topic: Algorithms

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Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.

PloS one
This study presents a novel research approach to predict user interaction for social media post using machine learning algorithms. The posts are converted to vector form using word2vec and doc2vec model. These two methods are used to analyse the best...

Early and Late Fusion Machine Learning on Multi-Frequency Electrical Impedance Data to Improve Radiofrequency Ablation Monitoring.

IEEE journal of biomedical and health informatics
Radiofrequency ablation (RFA) is a popular modality for tumor treatment. However, inexpensive real-time monitoring of RFA within multiple tissue types is still an ongoing research topic. The objective of this study is to utilize multi-frequency elect...

Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Existing works of analyzing clinical text data in the medical domain, which substantiate useful in...

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

JDR clinical and translational research
OBJECTIVES: Evaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral heal...

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...

Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Develop a high-performing algorithm to detect mesial temporal lobe (mTL) epileptiform discharges on intracranial electrode recordings.

DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...

Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery.

BioMed research international
Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into "usable...

Natural language processing of electronic health records is superior to billing codes to identify symptom burden in hemodialysis patients.

Kidney international
Symptoms are common in patients on maintenance hemodialysis but identification is challenging. New informatics approaches including natural language processing (NLP) can be utilized to identify symptoms from narrative clinical documentation. Here we ...

Optimized artificial neural network based performance analysis of wheelchair movement for ALS patients.

Artificial intelligence in medicine
Individuals with neurodegenerative attacks loose the entire motor neuron movements. These conditions affect the individual actions like walking, speaking impairment and totally make the person in to locked in state (LIS). To overcome the miserable co...