10 AI ML In Personal Healthcare Trends To Look Out For In 2024

Transforming Healthcare With AI

According to predictions, the worldwide market for artificial intelligence (AI) in healthcare would expand from an initial valuation of $15.1B in 2022 to more than $187.95B in 2030, a compound annual growth rate (CAGR) of 37 percent. The North American artificial intelligence healthcare industry was worth USD 6.8 billion in 2022.

By 2024, artificial intelligence is expected to make great strides in the medical field. Deep learning algorithms improve the accuracy of X-ray, MRI, and CT scan interpretation, which is useful in medical imaging and diagnostics. AI plays a crucial role in the drug discovery process by sifting through large datasets in search of promising compounds and automating development. Using a patient’s unique genetic and molecular profile, personalized medicine employs AI to create individualized treatment plans. Using natural language processing to glean insights from unstructured clinical data, predictive analytics helps with patient outcome prediction and at-risk population management.

The research examines six key areas where AI directly affects the patient and three sectors of the healthcare value chain that might gain from more scaling of AI. It also looks at specific instances of current AI solutions in healthcare.

With the help of AI, telemedicine and RPM may provide patients with up-to-the-minute health information. To guarantee ethical AI use, legislative frameworks, and ethical concerns have come to the fore. Instead of seeing AI as a replacement for human healthcare providers, the focus is on how AI systems may work in tandem with them. The picture highlights the revolutionary integration of AI into several aspects of healthcare, which holds great promise for better diagnoses, personalized treatments, and overall patient care.

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10 Personal Healthcare Trends To Look Out For In 2024

AI and ML are transforming personal healthcare by enhancing diagnostics, treatment, and overall wellness.

Here are 10 trends to watch out for in AI and ML in personal healthcare in 2024:

1. Personalized Treatment Plans: AI will analyze individual health data to create personalized treatment plans, including medication regimens and lifestyle recommendations. There will be an uptick in the number of chances for patients to get individualized healthcare in 2023. Precision medicine is a part of this, and it involves making individualized medicines and treatment plans for groups of patients based on characteristics like age, genetics, and risk factors, rather than using a cookie-cutter approach. By considering an individual’s genetic information, or genome, the most cutting-edge customized healthcare systems can assist doctors in determining the efficacy of medications and the likelihood of adverse effects. These forecasts are occasionally assisted by AI and ML systems.
2. AI for Mental Health: AI-driven mental health apps and platforms will provide therapy, counseling, and support for individuals dealing with mental health issues. Forecasts indicate that by 2023, the market for AI tools, particularly ML tools used in healthcare, will surpass $20 million. There is a lot of evidence that AI-aligned technologies like pattern recognition algorithms, computer vision, and natural language processing may improve healthcare. These technologies are now widely used in the industry and will only become more so as 2023 progresses. Drug discovery is one area where AI is used; it helps predict the results of clinical trials and the side effects of new drugs. Another area is medical imaging analysis, where AI is used to use computer vision algorithms to detect early warning signs of disease in X-rays or MRI scans. It has also shown promise in the diagnosis and treatment of neurological diseases, such as Alzheimer’s and Parkinson’s.
3. Wellness and Lifestyle Management: AI will help individuals make healthier choices by analyzing data from wearables and providing personalized fitness and nutrition guidance. In 2023, wearable technology will be more popular among both patients and doctors for remote patient monitoring and health and fitness tracking. Smartwatches that can do complex scans like electrocardiograms (ECGs), smart fabrics that can detect blood pressure and predict the likelihood of heart attacks, and smart gloves that can alleviate tremors experienced by Parkinson’s disease patients are just a few examples of the incredible growth of the “Internet of Medical Things” in the past few years. The development of wearable gadgets that can monitor and identify indicators of mental diseases is gaining attention alongside physical sickness. Medical wearables could soon include some of the features shown in research published this year that show how physical markers like sleep patterns, heart rate, and activity levels can be used to determine when someone might be at risk of depression.
4. Health Data Security: AI will strengthen data security by monitoring and identifying potential breaches and unauthorized access to personal health information. These trends indicate the increasing role of AI and ML in personal healthcare, with a focus on enhancing individual health, improving diagnoses, and making healthcare services more accessible and convenient. Staying informed about these developments will be crucial for individuals and healthcare professionals seeking to harness the benefits of AI and ML in healthcare in 2024 and beyond.
5. Remote Patient Monitoring: AI-powered wearables and devices will monitor patients’ health remotely, providing real-time data to healthcare providers for proactive care. Patients with non-emergency ailments may now see their physicians more quickly and inexpensively through remote, live video sessions utilizing their computers or mobile phones. This is due to the restricted access to healthcare staff. Patients can also message their doctors and organizations using telehealth technologies to ask questions about insurance or adjust their prescriptions. Additionally, it facilitates easy access to health education for patients. In addition, a patient’s whole medical history can be more easily accessible with telehealth systems as they enable the integration of data from various patient visits and test findings into electronic health records. Particularly for long-term health issues like hypertension and cardiovascular disease, telemedicine allows patients to stay active participants in their treatment when integrated with data from health wearables.
6. AI-Powered Virtual Assistants: Virtual health assistants will use AI to answer medical queries, provide health advice, and assist with appointment scheduling and medication reminders. Accenture found that 62 percent of those who use healthcare prefer virtual solutions. The same poll also indicated that 57% of people would prefer a way to have their chronic health conditions monitored remotely. Also, for regular checkups, 52% would choose virtual treatment. Given the chance, 42% of customers would “definitely or probably” go for a virtual option, even for disease diagnosis. Babylon Health and other health service companies are now offering new telehealth services.
7. Genomic Medicine: ML algorithms will assist in the interpretation of genomic data, aiding in the diagnosis and treatment of genetic conditions. Medications are usually made with a “one-size-fits-all” mentality, prioritizing maximum effectiveness with minimal adverse effects. Genomic research, digital twins, and artificial intelligence have all enabled doctors to take a more individualized approach, leading to medicines that are a perfect fit for each patient. While it has the potential to alleviate chronic pain effectively, it also carries the risk of side effects when taken in large quantities. Working together, pharmaceutical firms and healthcare facilities can develop individualized diagnostic and therapeutic instruments. Based on particular criteria such as blood sugar levels, personalized therapy offers individualized advice for exercise, nutrition, and disease management. It swiftly results in safe medications for long-term health problems like preventing heart attacks, arthritis, cancer, and Alzheimer’s.
8. Predictive Healthcare Analytics: AI will predict health trends and disease outbreaks, helping healthcare systems prepare for and mitigate health crises. Software like this may do things like remind patients of their next check-ins or find out if people tend to miss their appointments. Hospitals may enhance patient satisfaction and prevent staff overburden by optimizing wait times and staffing based on more accurate patient counts.
9. Drug Discovery: ML-driven drug discovery will accelerate the development of new pharmaceuticals, improving treatment options for various medical conditions. It can take a long time—and a lot of money—for pharma firms to bring a medicine to market. To save time and money, machine learning might sift through mountains of health-related or biological data for previously unseen insights. From the first idea to the final results of a medication study, machine learning is already an integral part of the process.
10. AI in Radiology: AI will continue to enhance radiological diagnostics, aiding radiologists in the detection of diseases and abnormalities with greater accuracy. The resolution of these photographs can be improved by artificial intelligence using upscaling algorithms. The use of image data augmentation techniques allows for the synthetic generation of data for these types of models. To complete the radiology workflow, other AI algorithms may be fed these improved pictures.

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Smart Use of Artificial Intelligence in Health Care

The MGI has investigated the potential effects of AI and automation on the future of employment. Healthcare is one of the industries with the least amount of time that might be automated—only 35% of the time, and this varies by job type—but automation will impact most employment across all industries to varying degrees. The possibility of automation and the probability of its implementation are distinct.

The research is based on a middle-ground scenario that predicts that 15% of healthcare workers’ current shifts will be automated. The following graphic displays, for a variety of healthcare vocations in certain European nations, the percentage of working hours that might be eliminated by automation by the year 2030. This doesn’t take into account the possibility of subsequent upheaval due to other variables, such as customization, which can transform healthcare by centering on a “portion of one.”

When it comes to healthcare, how many jobs will be eliminated by AI and automation? The truth is that there is a huge and predicted growing manpower gap in the European healthcare sector. As an example, the present supply of 8.6 million nurses, midwives, and healthcare assistants across Europe will not be enough to fulfill present or expected future demand, according to the World Health Organization, which forecasts overall need for healthcare professionals to climb to 18.2 million across Europe by 2030.4Care providers essential to the daily lives of European people, such as home health aides, licensed practical and vocational nurses, and others, will be in high demand in the future, according to MGI’s demand analysis of healthcare activities. It shows that automation has the potential to help with healthcare manpower shortages, as demand for healthcare jobs is expected to rise. For instance, even though around 10% of nursing tasks might be eliminated by automation, the overall number of nursing employment is projected to rise by 39% by 2030.

More than only employment gains or losses, the workforce will feel the effects of changes to the nature of work itself. Any shift in perspective is a chance to reevaluate and enhance patient care. Up to 70% of a healthcare provider’s time is devoted to mundane administrative duties; AI can assist in eliminating or significantly reducing this burden.

As a result, healthcare education will need to evolve to place more emphasis on creativity, entrepreneurship, lifelong learning, and collaboration across disciplines rather than rote memorization of data. The most significant shift will be the requirement for healthcare companies to include digital and AI capabilities. This includes training frontline employees to use AI in their daily tasks as well as doctors to alter the traditional consultation model. Practitioners, organizations, and systems must all work in tandem to bring about this massive shift in corporate culture and capabilities.

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