Shamla Mantri

Employment

• Dr. Vishwanath Karad MIT World Peace University, Department of Computer Engineering and Technology Associate professor
  2007 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (26)

• A deep learning approach to mild cognitive impairment detection from electroencephalogram signals
  Dementia & Neuropsychologia 2026 DOI: 10.1590/1980-5764-dn-2025-0364
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• AI-Powered Predictive Analytics for Market Trend Forecasting:  Integrating Deep Learning, NLP, and Ensemble Models for Enhanced Financial Insights
  Adroid Conference Series: Engineering and Technology 2026 DOI: 10.63503/acset.978-81-995593-9-4.49
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• Artificial Intelligence in Trucking Business Operations—A Systematic Review
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-99-9489-2_11
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• Deep Learning Approach for Early Diagnosis of Alzheimer’s Disease
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-99-9489-2_12
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• Exploring EEG-Based biomarkers for improved early Alzheimer's disease detection: A feature-based approach utilizing machine learning
  Measurement: Sensors 2024 DOI: 10.1016/j.measen.2024.101403
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• Recent Trends in Brain Tumor Prediction Using Machine Learning and Deep Learning
  Proceedings - 2024 IEEE 16th International Conference on Communication Systems and Network Technologies, CICN 2024 2024 DOI: 10.1109/CICN63059.2024.10847569
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• Women’s Safety Wearables Design Using An IoT-Based Framework Technology
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-99-9486-1_8
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• Comparative Analysis for Email Spam Detection Using Machine Learning Algorithms
  Lecture Notes in Electrical Engineering 2023 DOI: 10.1007/978-981-19-6383-4_2
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• Comparative Analysis of Human Hand Gesture Recognition in Real-Time Healthcare Applications
  Lecture Notes in Networks and Systems 2023 DOI: 10.1007/978-981-99-1745-7_33
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• Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach - A Review
  arXiv 2023 DOI: 10.48550/arXiv.2308.07052
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