The Internet of Medical Things is a system of medical devices and apps that connect to each other to collect, send, and study health information. These include wearable sensors, remote monitors, smart diagnostic tools, and mobile apps used for tracking health. IoMT lets healthcare providers watch patients from afar, lowering the need for frequent hospital visits for minor or long-term illnesses.
The COVID-19 outbreak sped up the use of IoMT to keep care going while avoiding in-person visits. For medical offices in the U.S., this change lowered the number of patients in clinics and gave more access to remote checkups and monitoring.
Important parts of IoMT in healthcare are medical sensors, 5G communication tech, cloud and edge computing, and especially Artificial Intelligence. AI looks at all the data from IoMT devices and finds useful information to help with medical decisions and daily tasks.
AI helps IoMT by making diagnoses better, personalizing care, and protecting data safety. AI programs can study large amounts of patient data, spot patterns, and guess health problems before symptoms get worse. This helps doctors create treatment plans that fit each patient using current and past data.
Natural Language Processing, a kind of AI, is useful for reading medical records and notes from patients. With NLP, AI can quickly understand data like doctor’s notes, lab results, or images to help doctors make better and more personalized diagnoses.
For example, Google’s DeepMind Health showed that AI can diagnose eye diseases from retinal scans as well as human experts. This shows how AI is becoming useful for finding diseases early and giving focused treatment.
AI also makes it easier to analyze patient data by combining information from different places and types in electronic health records used a lot in U.S. healthcare. Although it is hard to smoothly connect AI into these existing record systems, new developments are helping make it possible.
One big worry with using more IoMT devices is keeping patient information safe. Data leaks can harm patient privacy and the reputation of healthcare centers. AI helps with cybersecurity by noticing strange activities that could mean cyberattacks or hacks in IoMT systems.
AI security tools watch network actions and device behaviors all the time. They find risks faster than people can and can send warnings or start protective steps right away. For medical practice managers and IT staff, this AI security help is very important to follow rules like HIPAA and keep patient data safe.
Using AI with IoMT also helps automate healthcare work. Office managers and IT workers at medical places often have trouble managing appointment booking, patient contacts, billing, and other front-office jobs. AI tools can do repetitive and slow tasks, letting staff and doctors spend more time helping patients.
For example, Simbo AI uses AI to automate front-office calls and answering services for healthcare workers. Their system understands speech and language to answer calls 24/7, make appointments, give information, and sort requests without needing a person. This kind of automation cuts wait times, improves patient experience, and makes the office work better.
Also, AI chatbots and virtual helpers can keep patients involved all the time. They send reminders for medicine, give treatment instructions, and watch symptoms through connected IoMT devices. These tools help patients follow their care plans and notice early signs that need a doctor’s attention.
In medical offices, using AI to automate admin work lowers mistakes in data entry, speeds up communication inside and outside the office, and gives staff quick access to important information. This lets staff make decisions faster and lowers costs, which is very helpful for small to medium-sized offices competing in healthcare.
Personalized medicine is growing in the U.S., and AI in IoMT plays a key role. Instead of giving the same treatment to everyone, doctors can use AI to study genetic, clinical, and lifestyle data from IoMT devices and create treatment plans just for each patient.
AI’s machine learning looks at patient history and current health to predict risks of diseases getting worse. By finding patterns that could be missed, AI suggests ways to prevent problems and change treatments as needed. This helps patients get better results and lowers hospital visits.
AI can also study genetic data to find special mutations or markers. This lets doctors offer treatments based on a patient’s genetic profile, which is better than using general treatment rules.
Medical office managers gain from using AI that supports personalized care by improving patient satisfaction, making patients follow treatments, and getting better overall results. It also fits with value-based care systems growing in the U.S., where payment depends on patient health, not just services.
Experts such as Dr. Eric Topol of Scripps Translational Science Institute and Mara Aspinall of Illumina Ventures stress careful and responsible use of AI. They say collecting real-world data to prove AI’s benefits before wide use is important.
The AI market in healthcare is growing fast in the U.S. and worldwide. It was worth about $11 billion in 2021 and is expected to reach $187 billion by 2030. Big companies like IBM, Google, Microsoft, and Amazon are investing a lot in AI designed for healthcare.
A recent survey shows about 83% of U.S. doctors believe AI will help healthcare providers eventually. But 70% are careful about AI’s role in diagnosis, showing a need for careful checking and trust-building.
Centers with good infrastructure and AI systems lead progress. Still, medical offices across the U.S. need to find practical ways to add AI and IoMT step by step.
Medical offices in the United States can benefit from using AI and IoMT as part of their digital updates. By improving remote monitoring, automating tasks, helping personalized care, and boosting data security, these tools can handle rising healthcare demands. The work of managers, owners, and IT staff in choosing, applying, and managing these tools will shape how well AI and IoMT work in everyday patient care.
The IoMT is a sector within the Internet of Things (IoT) focused on healthcare, leveraging connected medical devices and applications to enhance patient care and health monitoring.
During the pandemic, the necessity for distanced healthcare prompted the use of IoMT devices, allowing for remote health monitoring and reducing the need for hospital visits for minor issues.
Key components include IoMT devices, medical sensors, artificial intelligence (AI), 5G, big data, edge computing, and cloud computing.
AI enhances IoMT systems by analyzing massive datasets for automated diagnostics, improving personalized care, and providing real-time disease management.
Sensors enable medical devices to securely transmit patient health data to server nodes, facilitating remote monitoring without human intervention.
AI assists in securing IoMT systems by detecting network intrusions and assessing web-based security using IoMT-enabled devices.
Research topics include AI-based IoMT applications, health monitoring and prediction, energy-efficient architecture, security and privacy issues, and data analytics.
The special issue aims to consolidate innovative research related to challenges and applications of AI-driven IoMT within smart healthcare.
The deadline for manuscript submissions is June 30, 2023.
The guest editors are Sidheswar Routray, Uttam Ghosh, Xingwang Li, and Khaled Rabie, representing various universities around the globe.
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