<?xml version="1.0" encoding="UTF-8"?><doi_batch version="4.3.7" xmlns="http://www.crossref.org/schema/4.3.7" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/schema/4.3.7 http://www.crossref.org/schema/deposit/crossref4.3.7.xsd">
		<head>
		<doi_batch_id>cirpublications.com-cyWw-1790899046-k510742301</doi_batch_id>
		<timestamp>1790899046</timestamp>
		<depositor>
			<depositor_name>Clinical Intelligence Research Press</depositor_name>
			<email_address>info@cirpublications.com</email_address>
		</depositor>
		<registrant>Clinical Intelligence Research Press</registrant>
	</head>
	<body>
		<journal>
			<journal_metadata>
				<full_title>Journal of Health Informatics and Digital Systems</full_title>
				<abbrev_title>J. Health Inform. Digit. Syst.</abbrev_title>
				<issn>3149-8973</issn>
			</journal_metadata>
			<journal_issue>
				<publication_date>
					<year>2025</year>
				</publication_date>
				<journal_volume>
					<volume>5</volume>
				</journal_volume>
				<issue>2</issue>
			</journal_issue>
			<journal_article publication_type="full_text">
				<titles>
					<title>Home Monitoring Adherence Verification Using Passive Signals: A Robust Missingness-Informed Detection Framework</title>
				</titles>
								<contributors>
          					<person_name sequence="first" contributor_role="author">
            <given_name>Fernando</given_name>
            <surname>Diaz</surname>
					</person_name>
          					<person_name sequence="additional" contributor_role="author">
            <given_name>Lucia</given_name>
            <surname>Morales</surname>
					</person_name>
          					<person_name sequence="additional" contributor_role="author">
            <given_name>Diego</given_name>
            <surname>Perez</surname>
					</person_name>
          				</contributors>
								<publication_date>
					<year>2025</year>
				</publication_date>
				<doi_data>
					<doi>10.68159/k510742301</doi>
					<resource>https://cirpublications.com/pub/journal/2/article/k510742301</resource>
				</doi_data>
				<citation_list>
          					<citation key="rk-10.68159/k510742301-0ee7c2a0-ae42-43d4-809e-67f1494d164f">
					  <unstructured_citation>Slade C, Sun Y, Chao WC, Chen CC, Benzo RM, Washington P. Current challenges and opportunities in active and passive data collection for mobile health sensing: a scoping review. JAMIA Open. 2025;8(4):ooaf025.</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-0779ff00-f60b-4769-a95a-9db41d59f827">
					  <unstructured_citation>van der Kamp MR, Hengeveld VS, Brusse-Keizer MGJ, Thio BJ, Tabak M. eHealth technologies for monitoring pediatric asthma at home: scoping review. J Med Internet Res. 2023;25:e45896.</unstructured_citation>
						 <doi>10.2196/45896</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-816baeee-6430-4da7-b6d1-a52d1fa95821">
					  <unstructured_citation>de Angel V, Lewis SY, White K, Oetzmann C, Leightley D, Oprea E, et al. Digital health tools for the passive monitoring of depression: a systematic review of methods. medRxiv. 2021;2021.07.19.21260786.</unstructured_citation>
						 <doi>10.1101/2021.07.19.21260786</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-c95fa41c-1128-4492-931a-fdfedd33ef7b">
					  <unstructured_citation>Jameil AK. High-performance hybrid AI systems with quantum-secure protocols for cyber-physical remote healthcare applications. Brunel Univ Lond. 2025.(thesis)</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-1cc23f2c-1799-4874-a169-4f71d0aa3061">
					  <unstructured_citation>Liu Y. Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and framework [thesis]. City Univ Hong Kong; 2025.</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-cdde12a9-c25c-4cf3-ac6f-949c8f8fa788">
					  <unstructured_citation>Salvi S, Garg L, Gurupur V. Stage-wise IoT solutions for Alzheimer’s disease: a systematic review of detection, monitoring, and assistive technologies. Sensors (Basel). 2025;25(17):5252.</unstructured_citation>
						 <doi>10.3390/s25175252</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-ad0a8502-d153-4ed1-b5c2-4a6940c10113">
					  <unstructured_citation>Mahmmod BM, Abdulhussain SH, Alrikabi HTS, Al-Jumaeily D, Hussien A. Patient monitoring system based on internet of things. Procedia Comput Sci. 2024;231:135-40.</unstructured_citation>
						 <doi>10.1016/j.procs.2023.12.066</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-760a2a5e-ffd7-44d4-83f3-3302dcf193c0">
					  <unstructured_citation>Bohlmann A, Mostafa J, Kumar M. Machine learning and medication adherence: scoping review. JMIRx Med. 2021;2(4):e26993.</unstructured_citation>
						 <doi>10.2196/26993</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-5fe9638a-9481-4e2a-99bf-50b0bfe59803">
					  <unstructured_citation>Laurent A. AI in remote patient monitoring: technology and applications. IntuitionLabs.ai. 2025.(report)</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-f347157a-232c-4099-b995-78d2096831a9">
					  <unstructured_citation>Washington P. Personalized machine learning using passive sensing and ecological momentary assessments for meth users in Hawaii: a research protocol. medRxiv. 2023;:2023.08.24.23294587.</unstructured_citation>
						 <doi>10.1101/2023.08.24.23294587</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-21d41366-676b-4e13-9046-d4f3e6278555">
					  <unstructured_citation>Dermody G, Wadsworth D, Dunham M, Glass C, Fritz R. Factors affecting clinician readiness to adopt smart home technology for remote health monitoring: systematic review. JMIR Aging. 2024;7:e64367.</unstructured_citation>
						 <doi>10.2196/64367</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-db28f4f6-4c20-4f49-9c57-a8f9229ff01c">
					  <unstructured_citation>Hartch CE, Dietrich MS, Lancaster BJ, Stolldorf DP, Mulvaney SA. Effects of a medication adherence app among medically underserved adults with chronic illness: a randomized controlled trial. J Behav Med. 2023.</unstructured_citation>
						 <doi>10.1007/s10865-023-00446-2</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-36f2487e-8b9a-44c3-a790-4adc15933e12">
					  <unstructured_citation>Patel PM, Green M, Tram J, Wang E, Murphy MZ, Abd-Elsayed A, et al. The role of AI-integrated remote patient monitoring in chronic disease management – a narrative review. J Pain Res. 2024;17:4223-37.</unstructured_citation>
						 <doi>10.2147/JPR.S494238</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-a85e21a5-cdf6-4062-8688-0eef66f94ce5">
					  <unstructured_citation>Rajmane D, Pawar M, Jagdale V, Patil S, Sayyad RM. IoT based smart medicine reminder. Int J Adv Res Sci Commun Technol. 2025;5(11).</unstructured_citation>
						 <doi>10.48175/568</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-4ab8e25b-61fa-48f3-b531-c5ee31246d1a">
					  <unstructured_citation>Sideri K, Cockbain J, Van Biesen W, De Hert M, Decruyenaere J, Sterckx S. Digital pills for the remote monitoring of medication intake: a stakeholder analysis and assessment of marketing approval and patent granting policies. J Law Biosci. 2022;9(2):lsac029.</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-f8896757-731b-4987-9cdb-54e53555d48e">
					  <unstructured_citation>Saeed DK, Nashwan AJ. Harnessing Artificial Intelligence in Lifestyle Medicine: Opportunities, Challenges, and Future Directions. Cureus. 2025;17(6):e85580.</unstructured_citation>
						 <doi>10.1177/15598276241241234</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-2d24f13b-0fb4-4abc-9658-0db4e1a814e8">
					  <unstructured_citation>Shaik MA. Advancing remote monitoring for patients with Alzheimer disease and related dementias: systematic review. J Nurs Scholarsh. 2025.(preprint)</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-f08f6e58-14e6-4e87-8161-79dc27236159">
					  <unstructured_citation>Salgueiro AJP. Parkinson’s disease classification and medication adherence monitoring using smartphone-based gait assessment and deep reinforcement learning algorithm. Procedia Comput Sci. 2021;185:246-53.</unstructured_citation>
						 <doi>10.1016/j.procs.2021.05.026</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-ab07b0e8-ba92-4c32-bf8f-fbf75e14fc64">
					  <unstructured_citation>Pyper E, McKeown S, Hartmann-Boyce J, Powell J. Digital health technology for real-world clinical outcome measurement using patient-generated data: systematic scoping review. J Med Internet Res. 2023;25:e46992.</unstructured_citation>
						 <doi>10.2196/46992</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-38af1969-f3c1-4a29-ac06-6fc941b5a026">
					  <unstructured_citation>Uppuluri V. Real-time monitoring of patient adherence using AI. Int J Health Sci. 2025;8(3):52-68</unstructured_citation>
											</citation>
          					<citation key="rk-10.68159/k510742301-f41be74f-e74c-4232-a3d3-157d670ff0e2">
					  <unstructured_citation>Momand Z, McCrum-Gardner E, McCrum-Gardner J. Building digital twins for elderly care: an end-to-end framework from data acquisition to modeling. IEEE Internet Things J. 2025;12(5):4567-89.</unstructured_citation>
						 <doi>10.1109/JIOT.2024.3358901</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-a74f334d-b34f-421d-8a32-7c61dc8be982">
					  <unstructured_citation>Babbar S, Babbar H. AI-powered multimodal analysis for early detection of neurodegenerative diseases using biomedical signals and behavioral biomarkers. IOSR J Pharm Biol Sci. 2025;20(2):27-40.</unstructured_citation>
						 <doi>10.9790/3008-2002022740</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-cc7ae88e-9748-4b89-b837-d28bed5d5907">
					  <unstructured_citation>Michels EAM, Gilbert S, Koval I, Wekenborg MK. Alarm fatigue in healthcare: a scoping review of definitions, influencing factors, and mitigation strategies. BMC Nurs. 2025;24(1):664.</unstructured_citation>
						 <doi>10.1186/s12912-025-03369-2</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-c6206471-3a4f-48c4-99d8-6b863ba0021b">
					  <unstructured_citation>Pozza M, Navarin N, Sakkalis V, Gabrielli S. Artificial intelligence methods and digital intervention strategies for predicting and managing chronic obstructive pulmonary disease exacerbations: an umbrella review. Healthcare (Basel). 2025;13(23):3037.</unstructured_citation>
						 <doi>10.3390/healthcare13233037</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-5082b3f8-dc88-46fa-9b2d-283c5da8a946">
					  <unstructured_citation>Qi W, Zhu X, Wang B, Shi Y, Dong C, Shen S, et al. Alzheimer’s disease digital biomarkers multidimensional landscape and AI model scoping review. npj Digit Med. 2025;8:366.</unstructured_citation>
						 <doi>10.1038/s41746-025-01640-z</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-ea63a8c6-e892-44e5-a80d-cca50374ea6c">
					  <unstructured_citation>Sharma N, Klein Brinke J, Van Gemert-Pijnen JEWCP, Braakman-Jansen LMA. Implementation of unobtrusive sensing systems for older adult care: scoping review. JMIR Aging. 2021;4(4):e27862.</unstructured_citation>
						 <doi>10.2196/27862</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-fb1d2054-23b9-4041-9e43-cca933dc49e2">
					  <unstructured_citation>Xu H, Mankoff J, Dey AK. Understanding practices and needs of researchers in human state modeling by passive mobile sensing. CCF Trans Pervasive Comput Interact. 2021;3:344-66.</unstructured_citation>
						 <doi>10.1007/s42486-021-00072-4</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-d667de8f-d361-4643-81c8-d6214b7723d4">
					  <unstructured_citation>Huang G, Chen X, Liao C. AI-driven wearable bioelectronics in digital healthcare. Biosensors (Basel). 2025;15(7):410.</unstructured_citation>
						 <doi>10.3390/bios15070410</doi> 					</citation>
          					<citation key="rk-10.68159/k510742301-a153c938-1aa5-4437-b19a-fe0a1b376c0d">
					  <unstructured_citation>Abernethy A, Adams L, Barrett M, Bechtel C, Brennan P, Butte A, et al. The promise of digital health: then, now, and the future. NAM Perspect. 2022.</unstructured_citation>
						 <doi>10.31478/202206e</doi> 					</citation>
          				</citation_list>
			</journal_article>
		</journal>
	</body>
</doi_batch>
