American Journal of Advanced Multidisciplinary Research and Innovation

E-ISSN: XXXX-XXXX   •   Impact Factor: -

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 5
September-October 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Advances in Machine Learning Applications Across Healthcare, Agriculture, and Environmental Sciences

Author(s) Thorsten Joachims
Country United States
Abstract Machine Learning (ML) has emerged as one of the most transformative technologies of the Fourth Industrial Revolution, enabling intelligent data-driven decision-making across multiple disciplines. Recent advances in Artificial Intelligence (AI), Deep Learning (DL), Computer Vision, Natural Language Processing (NLP), Internet of Things (IoT), Big Data Analytics, Cloud Computing, Edge Computing, Digital Twin Technology, Remote Sensing, Geographic Information Systems (GIS), Explainable Artificial Intelligence (XAI), Federated Learning, Precision Agriculture, Smart Healthcare, and Environmental Informatics have significantly expanded the applications of machine learning. These technologies facilitate disease diagnosis, crop yield prediction, environmental monitoring, disaster forecasting, precision farming, biodiversity conservation, and intelligent resource management, thereby supporting sustainable development and improving human well-being.
This study presents a comprehensive analysis of Advances in Machine Learning Applications Across Healthcare, Agriculture, and Environmental Sciences. A qualitative analytical research methodology based on secondary data is employed to investigate recent ML algorithms, interdisciplinary applications, technological innovations, and implementation challenges. The research evaluates how machine learning contributes to predictive analytics, intelligent automation, precision decision-making, sustainable agriculture, personalised healthcare, climate resilience, and environmental conservation.
The findings indicate that machine learning significantly enhances disease prediction, medical image analysis, precision farming, crop disease detection, water resource optimisation, biodiversity monitoring, air quality forecasting, and climate risk assessment. Deep learning models improve diagnostic accuracy in healthcare, while IoT-enabled ML systems optimise irrigation, fertiliser application, and pest management in agriculture. In environmental sciences, satellite imagery, remote sensing, and AI-based predictive models enable real-time ecosystem monitoring, carbon emission analysis, natural disaster prediction, and sustainable resource conservation.
Despite these opportunities, challenges remain concerning data quality, algorithm bias, model interpretability, computational complexity, privacy protection, cybersecurity, limited infrastructure in developing regions, and regulatory compliance. Future research should investigate explainable machine learning, federated learning, quantum machine learning, autonomous AI systems, multimodal environmental analytics, and green AI frameworks for sustainable innovation.
The study concludes that advances in machine learning provide a multidisciplinary technological foundation for intelligent healthcare, sustainable agriculture, and environmental management by integrating predictive analytics, digital technologies, and responsible artificial intelligence to support global sustainable development goals.
Keywords Machine Learning, Artificial Intelligence, Healthcare, Precision Agriculture, Environmental Sciences, Deep Learning, Explainable AI, Remote Sensing, Sustainable Development, Predictive Analytics.
Field Engineering
Published In Volume 2, Issue 5, September-October 2020
Published On 2020-10-05
View / Download PDF File

Share this



E-ISSN XXXX-XXXX
CrossRef

CrossRef DOI prefix of AJAMRI is 10.00000/AJAMRI

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About AJAMRI
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +1-872-302-3851 editor@ajamri.com