Machine Learning in Healthcare Analytics: A State-of-the-Art Review
The use of machine learning (ML) models have become a crucial factor in the growing field
of healthcare, ushering in a new era of medical research and diagnosis. This study …
of healthcare, ushering in a new era of medical research and diagnosis. This study …
LBCEPred: a machine learning model to predict linear B-cell epitopes
B-cell epitopes have the capability to recognize and attach to the surface of antigen
receptors to stimulate the immune system against pathogens. Identification of B-cell epitopes …
receptors to stimulate the immune system against pathogens. Identification of B-cell epitopes …
Machine learning techniques for identification of carcinogenic mutations, which cause breast adenocarcinoma
Breast adenocarcinoma is the most common of all cancers that occur in women. According
to the United States of America survey, more than 282,000 breast cancer patients are …
to the United States of America survey, more than 282,000 breast cancer patients are …
Aerial low‐altitude remote sensing and deep learning for in‐field disease incidence scoring of virus yellows in sugar beet
N Okole, FR Ispizua Yamati, R Hossain… - Plant …, 2024 - Wiley Online Library
This study investigates the potential of high‐resolution (< 0.5 cm/pixel) aerial imagery and
convolutional neural networks (CNNs) for disease incidence scoring in sugar beet, focusing …
convolutional neural networks (CNNs) for disease incidence scoring in sugar beet, focusing …
PseU-Pred: an ensemble model for accurate identification of pseudouridine sites
MT Suleman, YD Khan - Analytical Biochemistry, 2023 - Elsevier
Pseudouridine (ψ) is reported to occur frequently in all types of RNA. This uridine
modification has been shown to be essential for processes such as RNA stability and stress …
modification has been shown to be essential for processes such as RNA stability and stress …
The Sustainable Rural Industrial Development under Entrepreneurship and Deep Learning from Digital Empowerment
This paper aims to realize the planning of resource utilization and development of rural
industries endowed by digitalization under entrepreneurship. First, the global classic …
industries endowed by digitalization under entrepreneurship. First, the global classic …
Deep learning approaches for detection of breast adenocarcinoma causing carcinogenic mutations
Genes are composed of DNA and each gene has a specific sequence. Recombination or
replication within the gene base ends in a permanent change in the nucleotide collection in …
replication within the gene base ends in a permanent change in the nucleotide collection in …
New approaches in machine-based image analysis for medical oncology
Oncology research needs a huge quantity of images and test reports for diagnosing. In vitro
methods like computed tomography and magnetic resonance imaging, invivo methods like a …
methods like computed tomography and magnetic resonance imaging, invivo methods like a …
ORI-Deep: improving the accuracy for predicting origin of replication sites by using a blend of features and long short-term memory network
Replication of DNA is an important process for the cell division cycle, gene expression
regulation and other biological evolution processes. It also has a crucial role in a living …
regulation and other biological evolution processes. It also has a crucial role in a living …
DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation
Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which
can lead to cancer. Machine learning and deep learning methods have emerged as vital …
can lead to cancer. Machine learning and deep learning methods have emerged as vital …