@article{moudoudAdvancingPrivacyFairness2025,

title = {Advancing Privacy and Fairness in Healthcare Using Federated Edge Learning and Blockchain},

author = {H. Moudoud and Z. Abou El Houda and B. Brik},

url = {https://www.scopus.com/pages/publications/105012264671?origin=resultslist},

doi = {10.1109/JIOT.2025.3589179},

issn = {23274662 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {IEEE Internet of Things Journal},

volume = {12},

number = {22},

pages = {46129–46137},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {artificial intelligence (AI) has revolutionized many fields, including healthcare. The adoption of AI techniques in critical healthcare tasks, such as cancer diagnosis, holds great promise for revolutionizing the healthcare system. AI algorithms can be trained on vast datasets to recognize patterns, detect anomalies, and provide accurate assessments. However, the lack of realistic and up-to-date medical data poses a significant challenge to the widespread adoption of AI techniques. Additionally, privacy concerns surrounding sensitive medical data, particularly patient health records (PHRs), hinder data sharing among healthcare practitioners. This article aims to address these challenges by proposing a novel framework, entitled SecureMed, that uses federated learning (FL) and Blockchain to preserve privacy in the healthcare system. In particular, SecureMed consists of: 1) a novel distributed architecture that enables secure collaboration among multiple mobile edge computing (MEC)-based Internet of Medical Things (IoMT) devices, while ensuring the privacy of healthcare systems; 2) a fairness-aware FL solution to ensure that model performance is balanced across all participating healthcare institutions, addressing the issue of imbalanced data contributions; 3) a secure multiparty computation (SMPC) protocol to ensure secure aggregation of local model updates; and 4) a blockchain-based reputation model for collaborative FL training. The proposed framework leverages smart contracts to ensure trustworthiness, decentralization, and transparency in the FL process. The experimental results using the CIC IoMT dataset 2024 highlight the promising potential of SecureMed in revolutionizing healthcare systems. © 2014 IEEE.},

keywords = {Artificial intelligence algorithms, Artificial intelligence techniques, Block-chain, Blockchain, cancer diagnosis, Diagnosis, Distributed computer systems, Federated edge learning, Health care, Healthcare, Healthcare systems, Internet of medical thing, Internet of Medical Things (IoMT), Learning systems, Medical computing, Medical data, Network security, Privacy, Sensitive data},

pubstate = {published},

tppubtype = {article}

}

@article{savard_efficacy_2021,

title = {Efficacy of a stepped care approach to deliver cognitive-behavioral therapy for insomnia in cancer patients: A noninferiority randomized controlled trial},

author = {J. Savard and H. Ivers and M. -H. Savard and C. M. Morin and A. Caplette-Gingras and S. Bouchard and G. Lacroix},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121217599&doi=10.1093%2fsleep%2fzsab166&partnerID=40&md5=8c3390082d345b725c47465f96bb8e44},

doi = {10.1093/sleep/zsab166},

issn = {01618105 (ISSN)},

year  = {2021},

date = {2021-01-01},

journal = {Sleep},

volume = {44},

number = {11},

publisher = {Oxford University Press},

abstract = {Study Objectives: Cognitive-behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for cancer-related insomnia, but its accessibility is very limited in routine care. A stepped care approach has been recommended as a cost-effective way to make CBT-I more widely accessible. However, no controlled study has yet been published about the efficacy of this approach. The goal of this noninferiority randomized controlled trial (RCT) was to compare the short and long-term efficacy of a stepped care CBT-I (StepCBT-I) to a standard face-to-face CBT-I (StanCBT-I). Methods: A total of 177 cancer patients were randomized to: (1) StanCBT-I (6 face-to-face CBT-I sessions; n = 59) or (2) StepCBT-I (n = 118). In the StepCBT-I group, patients with less severe insomnia first received a web-based CBT-I (n = 65), while those with more severe insomnia received 6 face-to-face CBT-I sessions (n = 53). In both cases, patients could receive up to three booster sessions of CBT-I if they still had insomnia symptoms following this first step. Results: Results indicated that the Step-CBT-I group showed an Insomnia Severity Index score reduction and a sleep efficiency (on a sleep diary) increase that was not significantly inferior to that of StanCBT-I at all post-treatment time points. Analyses of secondary outcomes indicated significant time effects (ps <. 001) and no significant group-by-time interactions (ps from. 07 to. 91) on other sleep diary parameters, sleep medication use, depression, anxiety, fatigue, and quality of life scores. Conclusion(s): The efficacy of stepped care CBT-I is not inferior to that of a standard face-to-face intervention and is a valuable approach to making this treatment more widely accessible to cancer patients. Trial registration: ClinicalTrials.gov Identifier: NCT01864720 (https://clinicaltrials.gov/ct2/show/NCT01864720?term=Savard&draw=2&rank=6; Stepped Care Model for the Wider Dissemination of Cognitive-Behavioural Therapy for Insomnia Among Cancer Patients). © 2021 Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society.},

note = {Publisher: Oxford University Press},

keywords = {adult, Anxiety, Anxiety disorder, cancer, cancer diagnosis, cancer patient, cognitive behavioral therapy, Cognitive-behavioral therapy, comparative study, complication, controlled study, cost effectiveness analysis, Depression, disease severity, drug use, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30, fatigue, female, Hospital Anxiety and Depression Scale, human, Humans, insomnia, Insomnia Severity Index, long term care, major clinical study, male, malignant neoplasm, Middle Aged, Montreal cognitive assessment, neoplasm, Neoplasms, outcome assessment, procedures, psychotropic agent, quality of life, randomized controlled trial, remission, review, Self Care, short course therapy, sleep, sleep efficiency, Sleep Initiation and Maintenance Disorders, sleep pattern, stepped care, stepped care approach, Structured Clinical Interview for DSM Disorders, therapy effect, treatment outcome, web-based intervention},

pubstate = {published},

tppubtype = {article}

}

@article{savardEfficacySteppedCare2021,

title = {Efficacy of a stepped care approach to deliver cognitive-behavioral therapy for insomnia in cancer patients: A noninferiority randomized controlled trial},

author = {J. Savard and H. Ivers and M. -H. Savard and C. M. Morin and A. Caplette-Gingras and S. Bouchard and G. Lacroix},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121217599&doi=10.1093%2fsleep%2fzsab166&partnerID=40&md5=8c3390082d345b725c47465f96bb8e44},

doi = {10.1093/sleep/zsab166},

issn = {01618105 (ISSN)},

year  = {2021},

date = {2021-01-01},

journal = {Sleep},

volume = {44},

number = {11},

publisher = {Oxford University Press},

abstract = {Study Objectives: Cognitive-behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for cancer-related insomnia, but its accessibility is very limited in routine care. A stepped care approach has been recommended as a cost-effective way to make CBT-I more widely accessible. However, no controlled study has yet been published about the efficacy of this approach. The goal of this noninferiority randomized controlled trial (RCT) was to compare the short and long-term efficacy of a stepped care CBT-I (StepCBT-I) to a standard face-to-face CBT-I (StanCBT-I). Methods: A total of 177 cancer patients were randomized to: (1) StanCBT-I (6 face-to-face CBT-I sessions; n = 59) or (2) StepCBT-I (n = 118). In the StepCBT-I group, patients with less severe insomnia first received a web-based CBT-I (n = 65), while those with more severe insomnia received 6 face-to-face CBT-I sessions (n = 53). In both cases, patients could receive up to three booster sessions of CBT-I if they still had insomnia symptoms following this first step. Results: Results indicated that the Step-CBT-I group showed an Insomnia Severity Index score reduction and a sleep efficiency (on a sleep diary) increase that was not significantly inferior to that of StanCBT-I at all post-treatment time points. Analyses of secondary outcomes indicated significant time effects (ps <. 001) and no significant group-by-time interactions (ps from. 07 to. 91) on other sleep diary parameters, sleep medication use, depression, anxiety, fatigue, and quality of life scores. Conclusion(s): The efficacy of stepped care CBT-I is not inferior to that of a standard face-to-face intervention and is a valuable approach to making this treatment more widely accessible to cancer patients. Trial registration: ClinicalTrials.gov Identifier: NCT01864720 (https://clinicaltrials.gov/ct2/show/NCT01864720?term=Savard&draw=2&rank=6; Stepped Care Model for the Wider Dissemination of Cognitive-Behavioural Therapy for Insomnia Among Cancer Patients). © 2021 Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society.},

keywords = {adult, Anxiety, Anxiety disorder, cancer, cancer diagnosis, cancer patient, cognitive behavioral therapy, Cognitive-behavioral therapy, comparative study, complication, controlled study, cost effectiveness analysis, Depression, disease severity, drug use, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30, fatigue, female, Hospital Anxiety and Depression Scale, human, Humans, insomnia, Insomnia Severity Index, long term care, major clinical study, male, malignant neoplasm, Middle Aged, Montreal cognitive assessment, neoplasm, Neoplasms, outcome assessment, procedures, psychotropic agent, quality of life, randomized controlled trial, remission, review, Self Care, short course therapy, sleep, sleep efficiency, Sleep Initiation and Maintenance Disorders, sleep pattern, stepped care, stepped care approach, Structured Clinical Interview for DSM Disorders, therapy effect, treatment outcome, web-based intervention},

pubstate = {published},

tppubtype = {article}

}