Machine learning and deep learning predictive models for type 2 diabetes: a systematic review
L Fregoso-Aparicio, J Noguez, L Montesinos… - Diabetology & metabolic …, 2021 - Springer
Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …
above certain limits. Over the last years, machine and deep learning techniques have been …
Deep Convolution Neural Network sharing for the multi-label images classification
S Coulibaly, B Kamsu-Foguem, D Kamissoko… - Machine learning with …, 2022 - Elsevier
Addressing issues related to multi-label classification is relevant in many fields of
applications. In this work. We present a multi-label classification architecture based on Multi …
applications. In this work. We present a multi-label classification architecture based on Multi …
The secondary use of electronic health records for data mining: Data characteristics and challenges
The primary objective of implementing Electronic Health Records (EHRs) is to improve the
management of patients' health-related information. However, these records have also been …
management of patients' health-related information. However, these records have also been …
AI in healthcare: time-series forecasting using statistical, neural, and ensemble architectures
S Kaushik, A Choudhury, PK Sheron, N Dasgupta… - Frontiers in big …, 2020 - frontiersin.org
Both statistical and neural methods have been proposed in the literature to predict
healthcare expenditures. However, less attention has been given to comparing predictions …
healthcare expenditures. However, less attention has been given to comparing predictions …
A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID‐19 Cases from Chest X‐Ray Images
Background and Objective. The new coronavirus disease (known as COVID‐19) was first
identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and …
identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and …
Towards human-centric digital twins: leveraging computer vision and graph models to predict outdoor comfort
Conventional sidewalk studies focused on quantitative analysis of sidewalk walkability at a
large scale which cannot capture the dynamic interactions between the environment and …
large scale which cannot capture the dynamic interactions between the environment and …
Graph-based multi-label disease prediction model learning from medical data and domain knowledge
In recent years, the means of disease diagnosis and treatment have been improved
remarkably, along with the continuous development of technology and science …
remarkably, along with the continuous development of technology and science …
Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network
T Luo, C Zhou, F Chao - BMC bioinformatics, 2018 - Springer
Background Conventional methods of motor imagery brain computer interfaces (MI-BCIs)
suffer from the limited number of samples and simplified features, so as to produce poor …
suffer from the limited number of samples and simplified features, so as to produce poor …
iATC-NFMLP: Identifying Classes of Anatomical Therapeutic Chemicals Based on Drug Networks, Fingerprints, and Multilayer Perceptron
S Tang, L Chen - Current Bioinformatics, 2022 - ingentaconnect.com
Background: The Anatomical Therapeutic Chemicals (ATC) classification system is a widely
accepted drug classification system. It classifies drugs according to the organ or system in …
accepted drug classification system. It classifies drugs according to the organ or system in …
Deep ensemble model for classification of novel coronavirus in chest X‐ray images
The novel coronavirus, SARS‐CoV‐2, can be deadly to people, causing COVID‐19. The
ease of its propagation, coupled with its high capacity for illness and death in infected …
ease of its propagation, coupled with its high capacity for illness and death in infected …