Machine learning in mental health: a scoping review of methods and applications
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …
data applications for mental health, highlighting current research and applications in …
Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management
Biosensors are emerging as efficient (sensitive and selective) and affordable analytical
diagnostic tools for early-stage disease detection, as required for personalized health …
diagnostic tools for early-stage disease detection, as required for personalized health …
Survey on the objectives of recommender systems: Measures, solutions, evaluation methodology, and new perspectives
Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …
variety of commercial applications to help users find favourite products. Research in the …
Data mining algorithms and techniques in mental health: a systematic review
Data Mining in medicine is an emerging field of great importance to provide a prognosis and
deeper understanding of disease classification, specifically in Mental Health areas. The …
deeper understanding of disease classification, specifically in Mental Health areas. The …
Efficient user profiling based intelligent travel recommender system for individual and group of users
R Logesh, V Subramaniyaswamy… - Mobile Networks and …, 2019 - Springer
Abstract In recent times, Recommender Systems (RSs) are gaining immense popularity with
the wider adaptation to deal information overload problem in various application domains …
the wider adaptation to deal information overload problem in various application domains …
Stimuli-aware visual emotion analysis
Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing
tendency of expressing and understanding emotions through images on social networks …
tendency of expressing and understanding emotions through images on social networks …
Recognition of emotion intensities using machine learning algorithms: A comparative study
Over the past two decades, automatic facial emotion recognition has received enormous
attention. This is due to the increase in the need for behavioral biometric systems and …
attention. This is due to the increase in the need for behavioral biometric systems and …
[HTML][HTML] A hybrid mental health prediction model using Support Vector Machine, Multilayer Perceptron, and Random Forest algorithms
ES Mohamed, TA Naqishbandi, SAC Bukhari, I Rauf… - Healthcare …, 2023 - Elsevier
The prevalence and burden of mental health disorders are on the rise in conflict zones, and
if left untreated, they can lead to considerable lifetime disability. Following the repeal of …
if left untreated, they can lead to considerable lifetime disability. Following the repeal of …
Postpartum depression prediction through pregnancy data analysis for emotion-aware smart systems
Emotion-aware computing represents an evolution in machine learning enabling systems
and devices process to interpret emotional data to recognize human behavior changes. As …
and devices process to interpret emotional data to recognize human behavior changes. As …
Tourist recommender systems based on emotion recognition—a scientometric review
L Santamaria-Granados, JF Mendoza-Moreno… - Future Internet, 2020 - mdpi.com
Recommendation systems have overcome the overload of irrelevant information by
considering users' preferences and emotional states in the fields of tourism, health, e …
considering users' preferences and emotional states in the fields of tourism, health, e …