AI for Better Health: AI Applications in Healthcare

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Introduction
#1. Diagnostic Imaging and Radiology
#2. Electronic Health Records (EHR) Management
#3. Predictive Analytics and Risk Assessment
#4. Drug Discovery and Development
#5. Robotic Surgery and Assistance
#6. Virtual Nursing Assistants and Chatbots
#7. Mental Health and Behavioral Analysis
#8. Wearable Technology and Remote Monitoring
Closing Thoughts on AI Applications in Healthcare

AI for Better Health: AI Applications in Healthcare

Curated by

cdteliot

3 min read

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Artificial Intelligence (AI) is revolutionizing healthcare, offering innovative solutions for diagnosis, treatment, and patient care. As reported by the National Institutes of Health, AI applications in healthcare span from clinical decision support and personalized medicine to administrative tasks and drug discovery, promising to enhance efficiency, accuracy, and patient outcomes across the medical field.

#1. Diagnostic Imaging and Radiology

AI algorithms can assess medical images like X-rays, MRIs, radiographs, and CT scans, so they can discover even the subtlest of abnormalities such as lung nodules, brain tumors, and fractures

. Of course, the analysis of human radiologists holds more significance, but AI can help them detect problems that they may unknowingly miss

. AI can even identify patterns and features in the images that can help radiologists arrive at more precise interpretations

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#2. Electronic Health Records (EHR) Management

For EHR, Natural Language Processing (NLP) can extract information from clinical notes, automate routine tasks, and support diagnoses

. AI can really reduce the workload of healthcare professionals since it can handle administrative tasks

. It can step in for appointment scheduling and forming patient profiles

. It can also process patient records faster with speech recognition and smart data entry suggestions

. It can even raise diagnostic accuracy rates up to 98.7%

5 sources

#3. Predictive Analytics and Risk Assessment

Artificial intelligence systems can process the patient records and information fed into them. Machine learning algorithms examine vast amounts of patient data: their genetic information, medical history, lifestyle factors, and real-time monitoring data. Once done, they can identify current or possible illnesses, the progression of these diseases, and the appropriate treatment plans to improve the patient's health. AI can tell the patient what routine they should follow, the foods they can and cannot eat, the medications they must take, and even the proper resource allocation to afford the recommended treatments.

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#4. Drug Discovery and Development

Since drug formulation usually takes a long time, AI's assistance is needed across multiple stages, starting from target identification to clinical trial design

. There have been instances when AI was able to decrease costs and development times in the early stages by 25-50%

. This is possible because algorithms can inspect large datasets for drug targets. Afterward, they predict which properties the drug should have and generate new drug candidates entirely from scratch

. While AI can certainly be helpful when coming up with new drugs and medications, it still has shortcomings in model interpretability, data quality, and clinical validation

. Hopefully, these will be resolved in future innovations.

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#5. Robotic Surgery and Assistance

More and more operating rooms now have their own surgical robots. May it be general surgery or neurosurgery, these AI-powered machines can work alongside surgeons during complicated procedures.

It may seem frightening to let a robot operate on you, but this technology has already been proven and tested to the point that a surgical robot can do minimally invasive operations.

Sensors guide their robotic arms as AI analyzes real-time data from their cameras. They can improve visualization and even automate several surgical tasks.

An example of this is Intuitive Surgical's da Vinci system, which is already widely utilized for prostatectomies and hysterectomies.

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#6. Virtual Nursing Assistants and Chatbots

AI can now serve as your nurse 24/7. Packed with features that can assess your symptoms and answer basic health-related queries, chatbots can now attend to your immediate health concerns

. They can also set your doctor appointments and provide post-discharge care instructions and follow-ups

. The most noteworthy AI innovation in this area, though, is it can tackle initial triage with healthcare workers giving it an acceptance rate of 77.1%

. This way, AI can prioritize patients who are in need of urgent medical attention

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#7. Mental Health and Behavioral Analysis

Machine learning algorithms can evaluate various data types, including speech patterns, facial expressions, and social media activity, to determine any mental health issues

. In fact, AI can process text data and pinpoint linguistic markers associated with depression and anxiety

. It can even recognize certain behavioral patterns that indicate mental disorders

. Because of these, therapists can use the technology to come up with personalized treatment recommendations for their clients

. If you don't want to hire a therapist, there are even virtual therapy assistants and chatbots that you can tap for cognitive behavioral therapy anytime and anywhere

5 sources

#8. Wearable Technology and Remote Monitoring

AI can also track vital signs in real-time through devices that patients can put on such as biosensors and ECG monitors

. These wearables can continuously record physiological data such as heart rate, blood pressure, and glucose levels

. The data will be used by healthcare providers to assess any changes in the body and diagnose certain conditions for early detection and prevention

. This is very useful for those with chronic diseases since even slight changes in health status are crucial for such patients

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Closing Thoughts on AI Applications in Healthcare

AI has long since entered the healthcare arena and it brought improvements that can enhance medical systems and equipment. From diagnostic imaging to drug discovery, it assists healthcare professionals and gives them the leeway to focus on more important responsibilities.

These innovations certainly contribute to better patient outcomes and efficiency while keeping costs low, but like any form of technology, AI is not all-encompassing.

Doctors, nurses, and other medical staff should still employ their expert knowledge, skills, and experience even with how competent AI-enhanced tools are. AI can still make errors in diagnoses, fall short in data analysis, and even malfunction at times.

Human oversight is still essential to keep AI innovations useful and reliable for patient care and medical tasks.