Classification of hypothyroid disorder using optimized SVM method

VS Vairale, S Shukla - 2019 International Conference on Smart …, 2019 - ieeexplore.ieee.org
Hypothyroidism is an endocrine disorder where the thyroid organ doesn't provide the
enough amount of thyroid hormones. It is one of the common diseases found in women …

An ai driven approach for multiclass hypothyroidism classification

R Das, S Saraswat, D Chandel, S Karan… - … Conference on Advanced …, 2021 - Springer
Hypothyroidism is a condition when the thyroid gland produces less hormone than a normal
range. As the symptoms of hypothyroidism are not clear, in past days many researchers …

Optimized deformable model-based segmentation and deep learning for lung cancer classification

MV Shetty, S Tunga - The Journal of Medical Investigation, 2022 - jstage.jst.go.jp
Lung cancer is one of the life taking disease and causes more deaths worldwide. Early
detection and treatment is necessary to save life. It is very difficult for doctors to interpret and …

[PDF][PDF] Modelling effectivenes of IS learning methodology with AHP method

A Hehsan, J Junaidi, FM Yusof, H Abas… - Int. J. Eng …, 2018 - researchgate.net
Abstract Information system research methodology, Bahasa: Metodologi Penelitian Sistem
Informasi (MPSI), is a mandatory course that must be attended by information system and …

Short-term load forecasting of distributed energy system based on kernel principal component analysis and KELM optimized by fireworks algorithm

Y Fan, H Wang, X Zhao, Q Yang, Y Liang - Applied Sciences, 2021 - mdpi.com
Accurate and stable load forecasting has great significance to ensure the safe operation of
distributed energy system. For the purpose of improving the accuracy and stability of …

[PDF][PDF] Churn prediction in telecom using classification algorithms

G ApurvaSree, S Ashika, S Karthi… - International Journal of …, 2019 - academia.edu
Customershaveawiderangeoftelecomservic… industryandswitchingfromoneservicetoother…
[2], increasedcustomerchurnisalwaysamajorco… today [3]. Theaccuracyratealsomakesustoknowaboutt …

Diagnosing malaria from some symptoms: a machine learning approach and public health implications

HI Okagbue, PE Oguntunde, ECM Obasi… - Health and …, 2021 - Springer
Malaria is a leading cause of death in Nigeria and remains a public health concern because
of the increasing resistance of the disease to antimalarial drugs. Pregnant women and …

Quantum intelligence in medicine: Empowering thyroid disease prediction through advanced machine learning

M Sha - IET Quantum Communication, 2024 - Wiley Online Library
The medical information system is rich in datasets, but no intelligent systems can easily
analyse the disease. Recently, ML (Machine Learning)‐based algorithms have acted as a …

[HTML][HTML] Mineral prospectivity mapping using knowledge embedding and explainable ensemble learning: A case study of the Keeryin ore concentration in Sichuan …

S Yin, N Li, K Xiao, X Song, J Yin, C Wang - Ore Geology Reviews, 2024 - Elsevier
Abstract GIS-based Mineral Prospectivity Mapping (MPM) has been widely employed,
however, the absence of correlative interpretation between the final prospectivity maps and …

Exploring the Role of Green Microbes in Sustainable Bioproduction of Biodegradable Polymers

A Akinsemolu, H Onyeaka - Polymers, 2023 - mdpi.com
Research efforts have shifted to creating biodegradable polymers to offset the harmful
environmental impacts associated with the accumulation of non-degradable synthetic …