Transforming Healthcare With IoMT and Generative AI

Advances in healthcare information systems and administration book series, Journal Year: 2025, Volume and Issue: unknown, P. 83 - 114

Published: Jan. 17, 2025

The synergistic use of the IoMT and generative AI presents healthcare with practically brand-new approaches to long-standing problems. In this chapter, author demonstrates ideas how integrating real-time data gathering solution impact can increase effectiveness personal treatment, capacity identifying diseases avoiding them, organization services. By analyzing key applications introduced by such as surgical robot, remote health monitoring, virtual assistants it is possible evaluate technologies on positive patients' outcomes, decreased rate readmissions, increased engagement. addition, chapter explores technical issues ethical arising from application in privacy issues, integration call for proper regulations technologies.

Language: Английский

---

Revolutionizing Patient Care Through the Convergence of IoMT and Generative AI

Advances in healthcare information systems and administration book series, Journal Year: 2025, Volume and Issue: unknown, P. 217 - 242

Published: Jan. 17, 2025

The incorporation of the Internet Medical Things and Generative AI to this process shall transform patient care by offering continuous tracking, analysis individualized progression control. This chapter is dedicated synergistic fusion IoT in Technology (IoMT) Artificial Intelligence provides a brief summary what it is, how functions, can be expected future field health care. When combined with data acquiring capacity IoMT analytical potential AI, hospitals other medical facilities have bring diagnosis treatment higher level. Some real-life usage examples uses SDN are shown through different use cases, including chronic disease management, elderly care, virtual assistance, prognostic management maintenance healthcare facilities' equipment tools.

Language: Английский

---

Integration of Machine Learning Algorithms for Predictive Maintenance in IoT-Enabled Smart Safety Helmets

Published: May 24, 2024

Language: Английский

---

Enhanced Magnetic Resonance Imaging for Accurate Classification of Benign and Malignant Brain Cells

Published: May 24, 2024

Language: Английский

---

Cloud-Based Multi-Layer Security Framework for Protecting E-Health Records

Published: Dec. 29, 2023

The increasing role that cloud computing plays in storing e-health data has highlighted the necessity for strong security measures. purpose of this study is to shed light on difficulties protecting private health kept servers. As first priority, we developed a unique multi-layer architecture cloud-based protect electronic data. We provide complete analysis current protocols, perform vulnerability assessment, and create more robust multi-layered as part our methodology. concept includes sophisticated encryption methods, strict access rules, instruments ongoing threat detection. In order assess effectiveness framework, ran extensive simulations with an emphasis integrity, control, confidentiality. findings show considerable improvement over conventional, one-layer techniques. proposed framework guarantees regulatory compliance addition providing enhanced against illegal breaches. have found safeguarding records—which are critical both patients healthcare providers—requires approach built cloud. may lead improved future.

Language: Английский

---

Accurate Neoplasm Diagnosis with Comprehensive Machine Learning and Deep Learning Approaches

Published: May 24, 2024

Language: Английский

---

A Comprehensive AI-ML Study on Enhanced Classification of Benign and Malignant Cells in Brain MRI

Published: May 24, 2024

Language: Английский

---

Advancements in Multi-Cloud Applications for Enhanced E-Healthcare Services

Published: Dec. 29, 2023

E-Health Record Security Research on a Cloud-Based Multi-Layer Framework reaches its climax in string of noteworthy discoveries, demonstrating how the framework may transform cloud health data security. The framework's multi-tiered design proved to be an effective barrier against wide range cyber threats, protecting privacy and security patients' medical records. An important factor varied healthcare industry is fact that it can easily scaled adjusted meet needs providers sizes capabilities. Nevertheless, there are obstacles need addressed, according report. These include difficulty implementation ongoing for upgrades modifications address changing threats technical advances. Healthcare firms must continuously implement educational programs due reliance user compliance training. With eye toward future, this structure lays groundwork more sophisticated studies subject. Potential research directions improving cross-platform compatibility, optimizing resource utilization reduce performance implications, integrating AI ML automated threat response predictive analytics.

Language: Английский

---

Predictive Modeling of Dental Health Outcomes Based on Fluoride Concentrations using AI

Published: Dec. 29, 2023

Oral health is a crucial aspect of general health, and the presence fluoride in drinking water has been consistently linked to its improvement. This work utilizes deep learning machine approaches develop prediction models that can estimate oral consequences based on concentrations. Our analysis comprehensive dataset includes levels indicators from several geographic locations. The covers broad range demographic environmental factors. study involves thorough data pretreatment procedure, which activities such as cleaning, standardization, feature engineering. All these processes contribute improving making input variables more relevant. approach used encompasses algorithms, including neural networks, decision trees, ensemble approaches, are create models. Thoroughly adjusting hyperparameters using cross-validation methods maximize effectiveness model.

Language: Английский

---

Real-Time UV Radiation Monitoring and Analysis with Arduino and MATLAB for Enhanced Exposure Tracking

Published: March 15, 2024

This study a new system of real-time monitoring and analysing UV radiation using an integrated method is explored. It combines Arduino MATLAB technologies for data collection subsequent analysis respectively. The main purpose this work to summarize the roles levels, their changes in space time, efficiency different sunscreen methods. By developing sensor network along with algorithm, following able provide holistic views any given area's levels possible health effects exposure. research methodology we adopted includes acquisition information from various time location frames, which next followed by analytical phase evaluate effectiveness photoprotection tools including sunscreen, clothing, shade. In other words, examines association between exposure possibility obtaining skin damage, insisting on use protective measures. Integration alerting into app providing users dispatching notifications accordingly undoubtedly one crucial aspects research. These alerts are aimed at reminding apply measures that they deem suitable. outcomes unveils significant daily geographical variance exposure, identifying peak places major risk. On hand, comparative highlights practical benefits obtained after methods application; show explicitly risk increased damage increases UV. reaction important indicator alert strengthens its informing public guide them write right actions do avoid danger.

Language: Английский

---