# Enhancing Healthcare Informatics with Transparent and Explainable AI

**Authors:** Philip Eappen (Cape Breton University, Sydney, Nova Scotia, Canada) — ORCID 0000-0002-8120-8449; Narasimha Rao Vajjhala (Department of Computer Science, American University in Bulgaria, Blagoevgrad, Bulgaria) — ORCID 0000-0002-8260-2392; Ruiling Guo; Lucy Shinners; Virginia Gunn — ORCID 0000-0003-3104-9539
**Type:** Edited book
**Source:** Auerbach Publications (CRC Press), 280 pp.
**Published:** 2026-06-25
**DOI:** https://doi.org/10.1201/9781003604440
**Canonical page:** https://www.narasimharao.net/research/enhancing-healthcare-informatics-transparent-explainable-ai/
**Indexing:** Edited book · Scopus
**Methodology:** Edited volume of 11 chapters by international contributors; chapters range from ethical and conceptual analysis to systematic review (EEG analysis) and applied explainable-AI system descriptions.

## Research summary

- **The Problem:** Clinicians, patients and health workers will not rely on AI in healthcare informatics unless its decisions are explainable and transparent.
- **The Approach:** Edited volume of 11 chapters by international contributors; chapters range from ethical and conceptual analysis to systematic review (EEG analysis) and applied explainable-AI system descriptions.
- **The Core Contribution:** The volume applies explainable and transparent AI across clinical decision-making, telehealth, electronic health records, EEG analysis, wearable monitoring and mental health, pairing ethical analysis with applied systems and strategies for building trust.
- **The Citation:** Eappen, P., Vajjhala, N. R., Guo, R., Shinners, L., & Gunn, V. (Eds.). (2026). Enhancing Healthcare Informatics with Transparent and Explainable AI. Auerbach Publications (CRC Press). https://doi.org/10.1201/9781003604440

## Summary in detail

**Question.** How can explainable and transparent AI methods be applied across healthcare informatics — clinical decision-making, telehealth, electronic health records, monitoring and mental health — so that clinicians, patients and health workers can trust them?

**Scope.** The volume collects eleven chapters spanning the ethics of AI in healthcare, AI-driven decision-making in clinical settings, explainable AI in telehealth and the social factors of adoption, explainable multimodal systems for electronic health records and predictive analytics, personalisation, EEG analysis for harmful brain activity, AI for monitoring and wearable devices, explainable AI for the mental health of healthcare workers, AI in India’s healthcare transformation, and strategies to build patient and health-worker trust in AI mental-health care.

**Why it matters.** Healthcare differs from other domains where AI has succeeded: a recommendation about treatment must be explainable to the clinician and the patient. The book focuses specifically on transparency and explainability as the condition for safe adoption.

## What the book covers

1. Opens with an ethics chapter (AI and Nussbaum’s capabilities approach) and a chapter on AI-driven decision-making in clinical settings.
2. Extends explainability beyond the clinic to telehealth, considering social and developmental factors in AI adoption, and to explainable multimodal systems in electronic health records and predictive analytics.
3. Includes a systematic review of EEG analysis for identifying and classifying harmful brain activity, and chapters on AI for monitoring and wearable devices.
4. Addresses mental health twice: explainable AI for the mental health of healthcare workers, and the applications, promise, pitfalls and trust-building strategies of AI in mental health care.
5. Includes a regional chapter on AI in India’s healthcare transformation through collaboration.

## Book at a glance

| Item | Detail |
|---|---|
| Type | Edited book, 1st edition, 280 pages |
| Editors | Philip Eappen, Narasimha Rao Vajjhala, Ruiling Guo, Lucy Shinners, Virginia Gunn |
| Chapters | 11 |
| Themes | Ethics; clinical decision-making; telehealth; EHRs and predictive analytics; personalisation; EEG analysis; monitoring and wearables; mental health; national health-system transformation; trust |
| Publisher | Auerbach Publications, an imprint of CRC Press / Taylor & Francis |

## Contents

- AI Meets Nussbaum: Ethics for Smarter Healthcare — Barbara Gabriella Renzi and Giulio Napolitano
- AI-Driven Decision-Making in Clinical Settings — Tyler Pratt, Ruiling Guo, Christopher A. Partridge, and Christian H. Fredericksen
- Decision-Making Transparency Beyond Clinical Settings: Explainable AI Innovation in Telehealth and the Role of Social and Developmental Factors in AI Adoption — Virginia Gunn, Philip Eappen, and Theoneste Manishimwe
- Explainable Multimodal Systems in Electronic Health Records and Predictive Analytics — Prerna Mishra and Tausif Diwan
- Personalization in Healthcare Using AI — Pushpendra Kumar Verma, Gaurav Kumar, Paresh Pathak, and Shubham Kumar Sharma
- A Systematic Review of EEG Analysis for the Identification and Classification of Harmful Brain Activity — Pillaram Manoj Sanjay and S Sharmila Devi
- AI for Monitoring and Wearable Devices — Mitra Tithi Dey, Suman Patra, and Sucharita Mitra
- Explainable AI for Mental Health in Healthcare Workers — Monika Srivastava
- Artificial Intelligence in India’s Healthcare Revolution: Transforming Diagnostics and Personalized Care Through Collaboration — Jyoti Singh and Rajlaxmi Srivastava
- Artificial Intelligence for Health-Monitoring and Wearable Devices — Wasswa Shafik
- AI for Mental Health Care: Applications, Promise, Pitfalls, and Strategies to Build Patient and Health Worker Trust — Kathleen Nash, Lauren O’Donnell, Hikmat Singh Brar, Philip Eappen, and Virginia Gunn

## When this research may be relevant

This book may be relevant to researchers working on explainable AI (XAI) in medicine and health informatics, trustworthy clinical decision support, AI in telehealth and remote monitoring, AI and mental health, and ethics-led approaches to healthcare AI adoption.

## Limitations

- An edited collection: evidence and methods vary by chapter. Only the eBook ISBN is registered with Crossref; the publisher lists the first-published date as 2026 (Crossref 25 June 2026; the chapter pages state 3 August 2026).

## How to cite

Eappen, P., Vajjhala, N. R., Guo, R., Shinners, L., & Gunn, V. (Eds.). (2026). Enhancing Healthcare Informatics with Transparent and Explainable AI. Auerbach Publications (CRC Press). https://doi.org/10.1201/9781003604440

```bibtex
@book{eappen2026enhancing,
  title = {Enhancing Healthcare Informatics with Transparent and Explainable AI},
  editor = {Eappen, Philip and Vajjhala, Narasimha Rao and Guo, Ruiling and Shinners, Lucy and Gunn, Virginia},
  isbn = {9781003604440},
  edition = {1st},
  year = {2026},
  publisher = {Auerbach Publications (CRC Press)},
  doi = {10.1201/9781003604440},
  url = {https://doi.org/10.1201/9781003604440}
}
```