SPECIAL ISSUE OF BJIR JOURNAL
Convergence of Artificial Intelligence, Internet of Medical Things,
and Blockchain Technology for Next-Generation Precision Healthcare
and Intelligent Drug Delivery Systems
Lead Editor:
Engr. Dr. S M Nazmuz Sakib, CMSA®, FPWMP®, FTIP®, BIDA®, FMVA®, CBCA®
1. Executive Summary
The rapid proliferation of connected medical devices, advanced machine learning architectures, and distributed ledger technologies has created an unprecedented opportunity to transform healthcare from a reactive, episode-driven discipline into a proactive, data-driven ecosystem. Conventional healthcare systems operate in fragmented silos, limiting the depth of insight that clinicians can derive from patient data and impeding the development of genuinely personalized treatment pathways. This Special Issue addresses that gap by inviting rigorous, cross-disciplinary research that sits at the intersection of Artificial Intelligence (AI), the Internet of Medical Things (IoMT), and Blockchain Technology, with a particular emphasis on applications in precision oncology, remote patient monitoring, intelligent drug delivery, and secure health data governance.
The need for this synthesis is underscored by converging global trends: cancer incidence is projected to reach 35.3 million cases annually by 2050; wearable sensor markets are expanding at compound annual growth rates exceeding 20 percent; and healthcare data breaches continue to cost the global economy billions of dollars each year. AI offers predictive and diagnostic power, IoMT provides continuous physiological data streams, and Blockchain introduces the cryptographic trust required to federate sensitive patient records without centralised vulnerability. Together they constitute a technologically coherent and clinically actionable stack for next-generation precision healthcare.
2. Scope and Objectives
This Special Issue moves beyond isolated proof-of-concept studies to solicit work that demonstrates measurable clinical, engineering, or policy impact. Submissions are invited across the following thematic pillars:
AI-Driven Diagnostics and Biomarker Discovery: Application of deep learning, explainable AI (XAI), and large language models to the identification, validation, and clinical translation of oncological and cardiological biomarkers; mathematical modelling frameworks for tumour microenvironment co-evolution and therapy response prediction; radiomics and multi-omics data fusion pipelines.
IoMT and Wearable Sensor Networks for Remote Monitoring: Design, deployment, and evaluation of wearable and implantable IoMT devices for continuous physiological surveillance; signal processing and edge-AI approaches for real-time anomaly detection; interoperability standards and M2M communication protocols for heterogeneous sensor networks; digital-twin models of patient health trajectories.
Intelligent and Transdermal Drug Delivery Systems: Smart drug delivery architectures incorporating closed-loop feedback from biosensors; transdermal, microneedle, and iontophoretic platforms augmented by AI-driven dosing algorithms; computational pharmacokinetic modelling and personalised dosage optimisation; regulatory and biocompatibility considerations for next-generation delivery devices.
Blockchain-Secured Health Data Management: Smart-contract architectures for consent management, data provenance, and interoperable electronic health record (EHR) exchange; federated learning paradigms that preserve patient privacy while enabling multi-institutional model training; tokenised incentive structures for data contribution and auditability in clinical trials.
Cybersecurity and Resilience of Medical IoT Infrastructure: Threat modelling and intrusion detection for high-density edge medical networks; lightweight cryptographic protocols suitable for resource-constrained implantable and wearable devices; adversarial robustness of AI models deployed in clinical environments; regulatory and legal frameworks governing medical device cybersecurity.
Mathematical and Computational Foundations: Novel mathematical formulations supporting healthcare AI, including stochastic differential equation models for disease dynamics, topological data analysis applied to genomic and proteomic datasets, quantum-inspired optimisation for drug candidate screening, and category-theoretic approaches to composing interoperable clinical decision pipelines.
3. Theoretical Framework and Methodology
To ensure methodological coherence across contributions, the Special Issue is anchored by the following integrative frameworks:
The Precision Healthcare Convergence Model (PHCM): A triadic analytical lens that maps AI capability (predictive power, interpretability), IoMT data richness (sampling frequency, sensor modality diversity), and Blockchain trust (decentralisation index, smart-contract audit completeness) onto a unified patient-outcome surface. Contributors are encouraged to quantify their system using at least two of these three axes.
Federated Diagnostic Benchmarking (FDB): A privacy-preserving evaluation protocol in which model performance is assessed across distributed, non-shared datasets using standardised metric suites (AUC-ROC, F1, Brier score, calibration curves). Submissions involving clinical data are expected to provide FDB-compatible evaluation pipelines.
Adaptive Biomarker Integration Index (ABII): A composite scoring methodology for ranking the clinical readiness of AI-identified biomarkers, incorporating sensitivity and specificity at defined prevalence thresholds, regulatory pathway status, and reproducibility across independent cohorts.
Smart-Contract Verification Layer (SCVL): A formal verification framework for blockchain-based health data protocols that stress-tests consent withdrawal, audit trails, and cross-jurisdictional data transfer compliance before deployment, reducing the risk of legal challenge post-publication.
4. Significance and Impact
This Special Issue addresses several high-priority scientific and societal imperatives:
Clinical Translation Gap: By requiring authors to situate their contributions within clinically validated evaluation frameworks, the issue accelerates the pathway from laboratory prototype to bedside implementation.
Equitable Precision Medicine: Federated and blockchain-based approaches featured in this issue enable low-resource clinical settings in Asia, Africa, and Latin America to contribute to and benefit from globally trained AI models without surrendering data sovereignty.
Regulatory Intelligence: Contributions addressing smart-contract governance and AI explainability directly inform regulatory bodies developing frameworks for AI-as-a-Medical-Device (AIaMD) certification under evolving international standards.
Interdisciplinary Elevation: By uniting engineering mathematics, molecular biology, jurisprudence, and computer science, the issue broadens the methodological palette available to healthcare AI researchers and raises the citation and impact ceiling of participating journals.
SDG Alignment: The issue advances United Nations Sustainable Development Goal 3 (Good Health and Well-Being) and Goal 9 (Industry, Innovation, and Infrastructure) through evidence-based, technologically rigorous contributions.
5. Target Audience
Biomedical engineers and clinical informaticists working on wearable or implantable medical device development.
Oncologists, pharmacologists, and translational researchers investigating AI-assisted biomarker discovery and personalised therapy.
Computer scientists and mathematicians developing federated learning, blockchain protocols, or adversarial robustness techniques for healthcare applications Health economists, legal scholars, and policy analysts examining governance frameworks for AI-enabled medical technologies.
Pharmaceutical engineers designing next-generation transdermal, smart, or closed-loop drug delivery platforms.
Cybersecurity researchers focused on the integrity and resilience of connected medical device ecosystems.
6. Suggested Keywords for Submissions
Artificial Intelligence in Healthcare; Internet of Medical Things (IoMT); Blockchain Health Data; Federated Learning; Precision Oncology; Wearable Biosensors; Transdermal Drug Delivery; Explainable AI (XAI); Smart Contracts; Digital Twin Medicine; Cancer Biomarkers; Machine Learning Diagnostics; Network Security for Medical Devices; Mathematical Biomedical Modelling; Personalised Medicine; Remote Patient Monitoring; IoT Cybersecurity; Quantum-Inspired Algorithms
7. Timeline and Submission Process
Call for Papers Announcement: 01 August 2026
Submission Deadline: 30 September 2026
Peer Review Period: 01 October 2026 to 30 November 2026
Revision Deadline: 15 December 2026
Final Decision Notification: 22 December 2026
Anticipated Publication: 25 February 2027
All submissions must be original, previously unpublished work not under consideration elsewhere. Manuscripts should conform to the host journal’s author guidelines. Interdisciplinary submissions that span two or more of the thematic pillars defined in Section 2 are particularly encouraged. Authors are invited to submit a pre-submission inquiry of no more than one page outlining the proposed contribution to facilitate
8. Guest Editor’s Credentials
Engr. Dr. S M Nazmuz Sakib, CMSA®, FPWMP®, FTIP®, BIDA®, FMVA®, CBCA® holds the academic title of Professor of Science in Research and Development (Charter University) and has demonstrated sustained scholarly productivity across biomedical engineering, computational oncology, network security financial analytics, and environmental science.
His published contributions span internationally indexed journals and edited volumes including Springer Nature, Taylor and Francis (CRC Press), IGI Global, Wolters Kluwer, and multiple Asian Pacific and European scientific outlets. Peer-reviewed works directly relevant to this Special Issue include studies on DNA damage in cancer patients undergoing chemotherapy, the Microbiological Tumor Evolutionary Equation (MTEE), the MechanoTranscriptomic Gradient Alignment biomarker, hypofractionated radiotherapy outcomes in cerebral tumours, IoMT-based remote healthcare monitoring using wearable sensors, and blockchain technology for smart contracts and supply chain transparency.
His patent portfolio includes a registered transdermal insulin delivery apparatus (UK Design No. 6404343, valid 2024 to 2029), a network security managing device (India, 2024), a neuro-generative adversarial mechanism for real-time malware morphing detection in high-density edge networks (Germany, 2025), a machine learning-based personalised learning device (India, 2025), and a computing apparatus for analysing plant immunity (Australia, 2026). This breadth of inventive and scholarly output positions him as an integrative authority uniquely qualified to guide research at the convergence of AI, IoMT, and Blockchain in healthcare.
Dr. Sakib serves as Editorial Board Member of the Toxicology and Applied Pharmacology Insights (OPAST), the International Internal Medicine Journal (OPAST), the Journal of Environmental Monitoring and Assessment (Hill Publishing Group), the Babylonian Journal of Mathematics (Mesopotamian Academic Press), and additional interdisciplinary outlets. He holds six professional designations from the Corporate Finance Institute, is a Fellow of the Scholars Academic and Scientific Society, and is an Associate Member (Lifetime) of the Bangladesh Computer Society.
Contact: sakibpedia@gmail.com | ORCID: 0000-0001-9310-3014 | Scopus Author ID: 57227325898
Payment Details
The publication fee for accepted manuscripts is €400 for all types of papers. If your manuscript is accepted, payment must be made by bank transfer to the Austrian bank account, the details of which will be provided upon acceptance.
