The integration of big data and artificial intelligence technologies across industries has prompted wide-spread change.
Arguably every business and social service can utilize these technologies to improve the lives of millions, but nowhere is this more clear than in healthcare.
From the enhanced levels of accessibility offered by AI and big data processes to the newfound abilities of medical professionals to harness this data, technology is transforming the medical field. As a result, improved care solutions might just save lives across the world.
Now, big data gathered from the digitization of health records can be paired with AI analytical tools to offer scientists better insights into diseases and disabilities.
In the future, this technology will offer untold options for care and treatment.
In the meantime, here are 7 ways big data and AI are impacting healthcare, now and for the future.
We live in a pandemic-stricken world. COVID-19’s emergence altered the face of business and healthcare, emphasizing the need for remote options. Big data and AI tools have made such remote care possible through telemedicine.
Telemedicine is care received through virtual platforms—often video conferencing. In healthcare, telemedicine is used to increase accessibility, lower costs, and allow for social distancing. But where does big data and AI come in?
First, telemedicine can offer greater insights into a broader base of patients by increasing accessibility of care. With more patients seen, more data will be on-hand for medical researchers to study.
Second, advancements in AI and machine learning processes are improving all the time to help physicians catch and diagnose issues remotely. For example, FDNA is using facial recognition and AI learning to produce genomic insights. This can allow healthcare providers to catch a genetic disorder simply through a virtual call.
2. Disease Tracking and Prevention
As we have seen throughout the COVID-19 pandemic, big data plays a large role in disease tracking and prevention. Without the accumulation of vast stores of information, scientists would be at a loss for mapping the spread of disease and acting to prevent it.
Big data gives medical professionals the tools to learn exactly how illness spreads. Data analytics tools can track positive cases, death rate, and momentum across the world.
Then, AI-powered software can assist researchers in mapping and connecting related variables. This way, they can better uncover commonalities in infected individuals and treatment patterns.
AI and big data go hand-in-hand to help medical professionals understand how illness works, which in turn allows them to pass on valuable information to communities for disease prevention.
Healthcare data represents some of the most at-risk information when it comes to cyber-attacks. In 2019 alone, over 30 million patients were affected by data breaches in the U.S. medical industry. With AI integration, this risk will hopefully be reduced.
Artificial intelligence technology is improving the way data centers manage and secure data. In healthcare, this protection is sorely needed. AI systems can monitor servers to reduce the impact of overuse and idle functions, keeping a database running smoothly and reducing the risk of a breakdown or breach. Additionally, the ability of an AI to scan endpoints for potential unauthorized access to a system gives healthcare data an added level of protection.
In the future, tech like blockchains that link data through cryptographic hash functions might better enable healthcare facilities to store and secure data. For now, AI in cybersecurity is healthcare’s best defense.
4. The Internet of Healthcare Things
The Internet of Healthcare Things, or IoHT, is alive in wearable devices that scan and report medical data to physicians. Additionally, many healthcare technologies utilized in hospitals and care facilities access this online network of information. IoHT empowers a shared environment of data for better analysis and treatment, increasing the potential of care solutions.
IoHT and AI make smart devices possible. In the ICU, this can mean the difference between life and death. One machine, for example, uses AI to scan for deterioration that can mean the onset of sepsis. By alerting care providers to medical issues, smart devices cut response times and save lives.
5. Health Monitoring
Alongside the IoHT, health monitoring devices of all kinds receive a boost in functionality due to big data and AI systems. Patients can have their heart rate and vitals measured and reported for better care and screening. Additionally, the continued accrual of this data as more people use such devices will improve medical knowledge over time.
With more data, medical researchers can better create reliable models, further improving the ability of care providers to monitor health. By scanning for certain variables that indicate a health risk, physicians can catch problems early, potentially saving lives.
Additionally, clinical decision support tools can assist healthcare providers in making bed-side decisions that improve care. These tools leverage big data, pulling information, templates, and support all from a database made possible through the accumulation of patient data.
6. Risk Prediction and Treatment
But the ability to catch, prevent, and treat disease and illness does not stop at wearable devices and clinical decision support tools. The potential of big data to collate medical information—from symptoms to the success of treatments—offers the world valuable healthcare insights that transcend individual systems.
The enhanced accessibility of data on a large scale can provide medical professionals with the information they need to improve cures and treatments. Connecting variables that might have previously gone unnoticed in traditional record keeping allows for better indicators of risk for a wide variety of health issues. Then, physicians can implement a treatment plan proven to work efficiently based on similar patient data.
7. Screening and Diagnosis
The ability of big data and AI tech to aid in healthcare solutions is not limited to a physical location. Thanks to data and machine learning, everything from cancer to vision screenings can be conducted both at a physical office or through telemedicine. This allows physicians to diagnose and care for individuals wherever they are, eliminating risks for vulnerable individuals.
Without AI and big data tools—some free and cloud-based—care providers could not catch every problem in a screening with the same level of accuracy. It takes years of schooling to be able to diagnose certain health issues, but machine learning functions can analyze a person or image to provide a reliable answer instantly.
For example, a patient could learn through a telemedicine eye-care visit that they are at an increased risk for a brain tumor based on AI analysis. This would allow the patient to conduct additional care measures, potentially even saving their life. Without such advancements, healthcare solutions are limited to the fallibility of human endeavor.
Already, the impact of big data and AI has transformed the healthcare industry. Smart devices and telemedicine solutions are propagating through the accumulation and application of data. Meanwhile, medical professionals have a world of information to study and analyze for improved treatments and disease prevention.
The integration of AI in healthcare will never remove the human element of treatment in its entirety, but automated smart devices can assist providers in conducting the best of care.
For now, these innovations are just scratching the surface of usability in healthcare. In the future, the use of big data and AI could mean millions of lives saved, along with reduced costs for medical professionals and patients alike.
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