ArticleJournal of medical systems2017
iNICU - Integrated Neonatal Care Unit: Capturing Neonatal Journey in an Intelligent Data Way.
Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Edge-Hosted LLM-Assisted NICU Discharge Summary Generation: Field-Level Evaluation Using a Clinician-Defined Rubric.Healthcare (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Medical Education: Promise, Pitfalls, and Practical Pathways.Advances in medical education and practice · 2025Article
- Artificial intelligence for healthcare and medical education: a systematic review.American journal of translational research · 2023Review
- The path from big data analytics capabilities to value in hospitals: a scoping review.BMC health services research · 2022Article
- Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review.Journal of medical Internet research · 2021Review
- Designing a bed-side system for predicting length of stay in a neonatal intensive care unit.Scientific reports · 2021Article
- Development and validation of high definition phenotype-based mortality prediction in critical care units.JAMIA open · 2021Article
- Machine Learning-Based Automatic Classification of Video Recorded Neonatal Manipulations and Associated Physiological Parameters: A Feasibility Study.Children (Basel, Switzerland) · 2020Article
- Development of data dictionary for neonatal intensive care unit: advancement towards a better critical care unit.JAMIA open · 2020Article
- Quality improvement initiative for reduction of false alarms from multiparameter monitors in neonatal intensive care unit.Journal of education and health promotion · 2019Article
- Clutch Pedal Sensorization and Evaluation of the Main Parameters Related to Driver Posture.Sensors (Basel, Switzerland) · 2018Article
- Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices.Sensors (Basel, Switzerland) · 2018Article
- VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles.Sensors (Basel, Switzerland) · 2018Article
- Clinician-Driven Design ofIEEE journal of translational engineering in health and medicine · 2018Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neonatal period represents first 28 days of life, which is the most vulnerable time for a child's survival especially for the preterm babies. High neonatal mortality is a prominent and persistent problem across the globe. Non-availability of trained staff and infrastructure are the major recognized hurdles in the quality care of these neonates. Hourly progress growth charts and reports are still maintained manually by nurses along with continuous calculation of drug dosage and nutrition as per the changing weight of the baby. iNICU (integrated Neonatology Intensive Care Unit) leverages Beaglebone and Intel Edison based IoT integration with biomedical devices in NICU i.e. monitor, ventilator and blood gas machine. iNICU is hosted on IBM Softlayer based cloud computing infrastructure and map NICU workflow in Java based responsive web application to provide translational research informatics support to the clinicians. iNICU captures real time vital parameters i.e. respiration rate, heart rate, lab data and PACS amounting for millions of data points per day per child. Stream of data is sent to Apache Kafka layer which stores the same in Apache Cassandra NoSQL. iNICU also captures clinical data like feed intake, urine output, and daily assessment of child in PostgreSQL database. It acts as first Big Data hub (of both structured and unstructured data) of neonates across India offering temporal (longitudinal) data of their stay in NICU and allow clinicians in evaluating efficacy of their interventions. iNICU leverages drools based clinical rule based engine and deep learning based big data analytical model coded in R and PMML. iNICU solution aims to improve care time, fills skill gap, enable remote monitoring of neonates in rural regions, assists in identifying the early onset of disease, and reduction in neonatal mortality.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.