Effective multiple cancer disease diagnosis frameworks for improved healthcare using machine learning
Cancer is a kind of non-communicable disease, progresses with uncontrolled cell growth in
the body. The cancerous cell forms a tumor that impairs the immune system, causes other …
the body. The cancerous cell forms a tumor that impairs the immune system, causes other …
Effective prediction of bitcoin price using wolf search algorithm and bidirectional LSTM on internet of things data
Internet of things is the concept of establishing relationships and interactions with other
connected devices through a network to reach a specific objective. The collected data from …
connected devices through a network to reach a specific objective. The collected data from …
Efficient text summarization method for blind people using text mining techniques
S Basheer, M Anbarasi, DG Sakshi… - International Journal of …, 2020 - Springer
Owing to the phenomenal growth in communication technology, most of us hardly have time
to read books. This habit of reading is slowly diminishing because of the busy lives of …
to read books. This habit of reading is slowly diminishing because of the busy lives of …
Predicting autism spectrum disorder from associative genetic markers of phenotypic groups using machine learning
Abstract Machine learning is a discipline of artificial intelligence, geared towards the
development of various critical applications. Due to its high precision, it is widely adopted in …
development of various critical applications. Due to its high precision, it is widely adopted in …
Diagnosis of Mental Illness Using Deep Learning: a Survey
S Rajendran, R Gandhi, S Smruthi, S Chaudhari… - Artificial Intelligence for …, 2023 - Springer
Deep learning is a robust technique that aims to build systems that can improve
automatically based on experience using advanced statistical and probabilistic data. It has …
automatically based on experience using advanced statistical and probabilistic data. It has …
Molecular modeling of C1‐inhibitor as SARS‐CoV‐2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study
K Sekaran, R Polachirakkal Varghese… - Cell Biochemistry …, 2023 - Wiley Online Library
The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS‐CoV‐2),
a strain of COVID‐19, crumbled the global economic strength and caused a veritable …
a strain of COVID‐19, crumbled the global economic strength and caused a veritable …
Dimensionally improved residual neural network to detect driver distraction in real time
M Balamurugan, R Kalaiarasi - Journal of Physics: Conference …, 2021 - iopscience.iop.org
Bountiful reasons are there for crop up of road accidents. Predominantly most of the road
accidents are turn out by the humans. In compare with other sources of road accidents …
accidents are turn out by the humans. In compare with other sources of road accidents …
Predicting drug responsiveness by citalopram induced pathway regulations and biomarker discovery in lymphoblastoid cell lines from depression affected individuals
K Sekaran, S Shanmugam - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
Unipolar Disorder, more commonly identified as Major Depressive Disorder is a psychiatric
condition characterized by lack of interest, constant mood swings, and persistent feelings of …
condition characterized by lack of interest, constant mood swings, and persistent feelings of …
[PDF][PDF] Machine Learning Approaches for Obsessive Compulsive Disorder Detection
K Patel, AK Tripathy - The EuroBiotech Journal, 2023 - sciendo.com
Abstract Obsessive-Compulsive Disorder (OCD) is a psychiatric illness that produces
significant psychological distress in patients. Individuals with OCD have recurring unwanted …
significant psychological distress in patients. Individuals with OCD have recurring unwanted …
Regularization based discriminative feature pattern selection for the classification of Parkinson cases using machine learning
K Kaliyan, A Ganesan - Bio-Algorithms and Med-Systems, 2021 - degruyter.com
Objectives This paper focuses on developing a regularization-based feature selection
approach to select the most effective attributes from the Parkinson's speech dataset …
approach to select the most effective attributes from the Parkinson's speech dataset …