Senthilkumar Mohan

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it

Whom Senthilkumar Mohan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Resul Das

Who trusts Senthilkumar Mohan overall

1. Nafiseh Ghaffar Nia
2. Md Mamun Ali
3. Erkan Kaplanoglu
4. Bikash Kumar Paul
5. Amin Ul Haq
6. M. Ahsan

Papers from Senthilkumar Mohan's perspective

Ordered by how strongly the researchers Senthilkumar Mohan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Opposition-Based Learning: A New Scheme for Machine Intelligence (International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06))
2. Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing (IEEE Network)
3. Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques
4. Association rule mining to detect factors which contribute to heart disease in males and females (Expert systems with applications)
5. Effective diagnosis of heart disease through neural networks ensembles (Expert systems with applications)
6. ProfilIoT: a machine learning approach for IoT device identification based on network traffic analysis (ACM Symposium on Applied Computing)
7. Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules (Journal of King Saud University: Computer and Information Sciences)
8. Prediction of Heart Disease Using Machine Learning (2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA))
9. An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction (Expert systems with applications)
10. Wireless device identification with radiometric signatures (ACM/IEEE International Conference on Mobile Computing and Networking)

Their papers

• Artificial neural networks training algorithm integrating invasive weed optimization with differential evolutionary model (2021) — 316 citations
• Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques (2019) — 1,389 citations