AIMC Topic: Humans

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Unsupervised neural network for evaluating the ability of the SF-36 instrument to differentiate individuals.

Eastern Mediterranean health journal = La revue de sante de la Mediterranee orientale = al-Majallah al-sihhiyah li-sharq al-mutawassit
BACKGROUND: Health-related quality of life (HRQoL) and well-being refer to the positive, subjective state that is contrary to illness. HRQoL instruments include some common questionnaires, which may often be understood differently depending on the le...

Incremental Learning to Personalize Human Activity Recognition Models: The Importance of Human AI Collaboration.

Sensors (Basel, Switzerland)
This study presents incremental learning based methods to personalize human activity recognition models. Initially, a user-independent model is used in the recognition process. When a new user starts to use the human activity recognition application,...

Deep biomarkers of aging and longevity: from research to applications.

Aging
Multiple recent advances in machine learning enabled computer systems to exceed human performance in many tasks including voice, text, and speech recognition and complex strategy games. Aging is a complex multifactorial process driven by and resultin...

TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology.

BMC bioinformatics
BACKGROUND: The Gene Ontology (GO) knowledgebase is the world's largest source of information on the functions of genes. Since the beginning of GO project, various tools have been developed to perform GO enrichment analysis experiments. GO enrichment...

Attention-based recurrent neural network for influenza epidemic prediction.

BMC bioinformatics
BACKGROUND: Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat to the society, precise real-time forecasting of influenza outbreaks is of great value to our public.

Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Computational intelligence and neuroscience
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training bas...

Different spexin level in obese vs normal weight children and its relationship with obesity related risk factors.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Spexin (SPX) is a novel peptide recently discovered as an important regulatory adipokine in obesity and related metabolic diseases. The aim of the current study was to determine the potential role of Circulating levels of SPX in ...

The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

Skeletal radiology
OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray feat...

Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization.

Medical image analysis
Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities. Based on CBCT images, it is clinically essential to generate an accurate 3D mo...