Fall prediction using behavioural modelling from sensor data in smart homes
Sign Up to like & getrecommendations! Published in 2019 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-019-09687-7
Abstract: The number of methods for identifying potential fall risk is growing as the rate of elderly fallers continues to rise in the UK. Assessments for identifying risk of falling are usually performed in hospitals and… read more here.
Keywords: sensor data; risk; fall prediction; prediction using ... See more keywords
Seismic activity prediction using computational intelligence techniques in northern Pakistan
Sign Up to like & getrecommendations! Published in 2017 at "Acta Geophysica"
DOI: 10.1007/s11600-017-0082-1
Abstract: Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability… read more here.
Keywords: computational intelligence; prediction using; northern pakistan; neural network ... See more keywords
A novel approach for disease comorbidity prediction using weighted association rule mining
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-019-01217-1
Abstract: Disease comorbidity prediction has gained the attention of many researchers during the past years. Bulk creation of clinical data in the form of electronic health records (EHRs) and biological data opened the door to explore… read more here.
Keywords: prediction using; comorbidity prediction; comorbidity; disease ... See more keywords
Multi-channel fusion LSTM for medical event prediction using EHRs
Sign Up to like & getrecommendations! Published in 2022 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2022.104011
Abstract: Automatic medical event prediction (MEP), e.g. diagnosis prediction, medication prediction, using electronic health records (EHRs) is a popular research direction in health informatics. In many cases, MEP relies on the determinations from different types of… read more here.
Keywords: event; fusion; prediction using; prediction ... See more keywords
Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of hazardous materials"
DOI: 10.1016/j.jhazmat.2020.123492
Abstract: Lead (Pb) is a primary toxic heavy metal (HM) which present throughout the entire ecosystem. Some commonly observed challenges in HM (Pb) prediction using artificial intelligence (AI) models include overfitting, normalization, validation against classical AI… read more here.
Keywords: prediction using; study; model; heavy metal ... See more keywords
Fragment Linker Prediction Using the Deep Encoder-Decoder Network for PROTACs Drug Design
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.2c01287
Abstract: Drug discovery and development pipeline is a prolonged and complex process and remains challenging for both computational methods and medicinal chemists. Deep learning has shed light on various fields and achieved tremendous success in designing… read more here.
Keywords: network; prediction using; linker prediction; design ... See more keywords
Global Analysis of Deep Learning Prediction Using Large-Scale In-House Kinome-Wide Profiling Data
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c00664
Abstract: In drug discovery, the prediction of activity and absorption, distribution, metabolism, excretion, and toxicity parameters is one of the most important approaches in determining which compound to synthesize next. In recent years, prediction methods based… read more here.
Keywords: house; prediction using; prediction; deep learning ... See more keywords
Protein design and variant prediction using autoregressive generative models
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-22732-w
Abstract: The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for important applications where… read more here.
Keywords: prediction using; design variant; protein design; variant prediction ... See more keywords
Diabetes prediction using machine learning and explainable AI techniques.
Sign Up to like & getrecommendations! Published in 2022 at "Healthcare technology letters"
DOI: 10.1049/htl2.12039
Abstract: Globally, diabetes affects 537 million people, making it the deadliest and the most common non-communicable disease. Many factors can cause a person to get affected by diabetes, like excessive body weight, abnormal cholesterol level, family… read more here.
Keywords: using machine; prediction using; machine learning; diabetes prediction ... See more keywords
Liquefaction prediction using CPT data by triangular chart identification
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Geotechnical Engineering"
DOI: 10.1080/19386362.2017.1282399
Abstract: Cone Penetration Test (CPT) is a common in-situ test renowned in liquefaction prediction. Description, deterministic and probabilistic models are used for predicting the occurrence of soil liquefaction. In this paper, new format of classification charts,… read more here.
Keywords: cpt data; liquefaction; prediction using; liquefaction prediction ... See more keywords
Sea level prediction using ARIMA, SVR and LSTM neural network: assessing the impact of ensemble Ocean-Atmospheric processes on models’ accuracy
Sign Up to like & getrecommendations! Published in 2021 at "Geomatics, Natural Hazards and Risk"
DOI: 10.1080/19475705.2021.1887372
Abstract: This study aims to integrate a broad spectrum of ocean-atmospheric variables to predict sea level variation along West Peninsular Malaysia coastline using machine learning and deep learning techniq... read more here.
Keywords: using arima; sea level; prediction using; ocean atmospheric ... See more keywords