A Study on Internet of Things in Women and Children Healthcare

• URL: http://arxiv.org/abs/2407.20237v1
• Date: Sun, 14 Jul 2024 17:34:00 GMT
• Title: A Study on Internet of Things in Women and Children Healthcare
• Authors: Nishargo Nigar,
• Abstract summary: Internet of Things (IoT) has the capability of collecting patient data incessantly. Doctors can diagnose their patients early to avoid complications and they can suggest further modifications if needed. This paper describes several methods, practices and prototypes regarding IoT in the field of healthcare for women and children.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Individual entities are being connected every day with the advancement of Internet of Things (IoT). IoT contains various application domains and healthcare is one of them indeed. It is receiving a lot of attention recently because of its seamless integration with electronic health (eHealth) and telemedicine. IoT has the capability of collecting patient data incessantly which surely helps in preventive care. Doctors can diagnose their patients early to avoid complications and they can suggest further modifications if needed. As the whole process is automated, risk of errors is reduced. Administrative paperwork and data entry tasks will be automated due to tracking and connectivity. As a result, healthcare providers can engage themselves more in patient care. In traditional healthcare services, an individual used to have access to minimal insights into his own health. Hence, they were less conscious about themselves and depended wholly on the healthcare facilities for unfortunate events. But they can track their vitals, activities and fitness with the aid of connected devices now. Furthermore, they can suggest their preferred user interfaces. This paper describes several methods, practices and prototypes regarding IoT in the field of healthcare for women and children.

Related papers

• Secure Wearable Apps for Remote Healthcare Through Modern Cryptography [1.693687279684153]
  Wearable devices like smartwatches, wristbands, and fitness trackers are designed to be lightweight devices to be worn on the human body. With the increased connectivity of wearable devices, they will become integral to remote healthcare solutions. This paper explores solutions for applying modern cryptography to secure wearable apps.
  arXiv  Detail & Related papers  (2024-10-10T05:50:12Z)
• Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Survey [53.691704671844406]
  The Internet of things (IoT) can significantly enhance the quality of human life, specifically in healthcare. The human digital twin (HDT) is proposed as an innovative paradigm that can comprehensively characterize the replication of the individual human body. HDT is envisioned to empower IoT-healthcare beyond the application of healthcare monitoring by acting as a versatile and vivid human digital testbed. Recently, generative artificial intelligence (GAI) may be a promising solution because it can leverage advanced AI algorithms to automatically create, manipulate, and modify valuable while diverse data.
  arXiv  Detail & Related papers  (2024-01-22T03:17:41Z)
• Yes, this is what I was looking for! Towards Multi-modal Medical Consultation Concern Summary Generation [46.42604861624895]
  We propose a new task of multi-modal medical concern summary generation. Nonverbal cues, such as patients' gestures and facial expressions, aid in accurately identifying patients' concerns. We construct the first multi-modal medical concern summary generation corpus.
  arXiv  Detail & Related papers  (2024-01-10T12:56:47Z)
• The Design and Implementation of a National AI Platform for Public Healthcare in Italy: Implications for Semantics and Interoperability [62.997667081978825]
  The Italian National Health Service is adopting Artificial Intelligence through its technical agencies. Such a vast programme requires special care in formalising the knowledge domain. Questions have been raised about the impact that AI could have on patients, practitioners, and health systems.
  arXiv  Detail & Related papers  (2023-04-24T08:00:02Z)
• Mental Illness Classification on Social Media Texts using Deep Learning and Transfer Learning [55.653944436488786]
  According to the World health organization (WHO), approximately 450 million people are affected. Mental illnesses, such as depression, anxiety, bipolar disorder, ADHD, and PTSD. This study analyzes unstructured user data on Reddit platform and classifies five common mental illnesses: depression, anxiety, bipolar disorder, ADHD, and PTSD.
  arXiv  Detail & Related papers  (2022-07-03T11:33:52Z)
• When Accuracy Meets Privacy: Two-Stage Federated Transfer Learning Framework in Classification of Medical Images on Limited Data: A COVID-19 Case Study [77.34726150561087]
  COVID-19 pandemic has spread rapidly and caused a shortage of global medical resources. CNN has been widely utilized and verified in analyzing medical images.
  arXiv  Detail & Related papers  (2022-03-24T02:09:41Z)
• Secure Multi-Party Computation based Privacy Preserving Data Analysis in Healthcare IoT Systems [0.0]
  Data transferred to the digital environment pose a threat of privacy leakage. In this study, it is aimed to propose a model to handle the privacy problems based on federated learning. Our proposed model presents an extensive privacy and data analysis and achieve high performance.
  arXiv  Detail & Related papers  (2021-09-29T10:39:25Z)
• Internet-of-Things Devices and Assistive Technologies for Healthcare: Applications, Challenges, and Opportunities [5.8497361730688695]
  Hospitals and clinics no longer have the ability to accommodate large numbers of incoming patients. It is clear that the current state of the health industry needs to improve its valuable and limited resources. The evolution of the Internet of Things (IoT) devices along with assistive technologies can alleviate the problem in healthcare.
  arXiv  Detail & Related papers  (2021-07-11T12:18:12Z)
• Detection and Prediction of Infectious Diseases Using IoT Sensors: A Review [0.0]
  There are many interactive hardware platform packages like IoT in healthcare. The most considerable advantage to IoT in healthcare is that it supports doctors in undertaking extra significant clinical work. This paper investigates the basis exploration of the applicability of IoT in the healthcare System.
  arXiv  Detail & Related papers  (2021-01-02T15:59:00Z)
• A Review on Security and Privacy of Internet of Medical Things [1.6099403809839032]
  The Internet of Medical Things (IoMT) are increasing the accuracy, reliability, and the production capability of electronic devices. Sensors, wearable devices, medical devices, and clinical devices are all connected to form an ecosystem of the Internet of Medical Things.
  arXiv  Detail & Related papers  (2020-09-11T12:31:40Z)
• Self-Attention Enhanced Patient Journey Understanding in Healthcare System [43.11457142941327]
  MusaNet is designed to learn the representations of patient journeys that is used to be a long sequence of activities. The MusaNet is trained in end-to-end manner using the training data derived from EHRs. Results have demonstrated the proposed MusaNet produces higher-quality representations than state-of-the-art baseline methods.
  arXiv  Detail & Related papers  (2020-06-15T10:32:36Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.