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AlmaBetter Blogs > Role of Big Data Analytics and AI in the future of healthcare

Role of Big Data Analytics and AI in the future of healthcare

Data Science
Healthcare is one of the fastest-growing growing parts of the economy. The world is going through a pandemic, and all eyes are on the industry and the new inventions that could save millions of lives.
Role of Big Data Analytics and AI in the future of healthcare

Healthcare organizations worldwide are turning to advanced techniques such as Artificial Intelligence, Machine Learning, and Big Data to help make healthcare practices more efficient.

Data and information have always been essential for decision-making and healthcare provision. With improved digitization in healthcare, a massive amount of data is also generated from other healthcare industry segments than hospitals and healthcare providers, for example, medical insurance, medical equipment, life sciences, and medical research.

It is safe to say that AI promises a better future in healthcare. According to a research conducted by Acumen, the global healthcare market will hit $8 billion by 2026.

This blog will look at how AI and Big Data are used in healthcare.

AI Battles Serious Illness with Better Predictions

AI and big data deliver great value by boosting the speed with which scientists and healthcare experts can process and use data. With the use of analytical techniques, healthcare stakeholders can harness the power of data not only for the analysis of historical data but also for predicting future outcomes and selecting the most suitable action for the current situation. By integrating life sciences with big data, a company can battle dangerous conditions like cancer and cardiovascular disease. Here are some examples:

  • Developing machine learning algorithms and devices to predict the risk of cardiovascular disease before it transpires.
  • Increasing the accuracy of osteoporosis risk predictions in women, thereby lowering the risk window from ten years to two.

New Drug Discovery

According to Daphne Koller, ML researcher and founder of Insitro, Big pharma is finding it challenging to develop new drugs. Over the past few decades, developing drugs has become increasingly more problematic and costly, leaving patients with substantial unmet needs. According to a report, it can take up to 15 years to bring a new and potentially life-saving drug to market. However, AI technology can help researchers find the right participants for clinical trials and experiments which can boost the process. The technology can also help the experimenters monitor their medical responses more accurately and efficiently.

Utilizing Big Data To Fight Cancer

Big Data technology can also be beneficial in the fight against cancer. According to a report published by National Geographic, big data technologies can identify and reveal hidden patterns resulting in early detection of cancer. Early diagnosis of the condition can increase the chances of treating it. Big data technologies are proficient at interpreting genome sequencing to identify biomarkers for cancer and reveal groups at higher risk of cancer and find otherwise undiscovered treatments. The most advanced companies use big data techniques to speed their analyses and develop treatments faster and with more tangible results.

Detecting Healthcare Fraud

According to research from a Splunk report titled AI and ML in regulated industries, detecting and discovering patterns of strange and concerning behavior among many healthcare providers is complex and very time-consuming. Uncovering the source of illegal prescriptions and monitoring it more closely is an additional challenge. With machine learning programs and algorithms, healthcare organizations can see patterns across that data and when they deviate, allowing healthcare organizations to shift to preventing and identifying fraud versus a “pay and chase” approach.

Quality of Electronic Health Records (EHR)

Conventionally, doctors would manually write down or type remarks and patient data after the patient’s visit, resulting in human error. However, with AI and deep learning-backed speech recognition technology, interactions with patients, clinical diagnoses, and potential treatments can be augmented and registered more accurately and in near real-time.

Enhancing Population Health

Big data is playing a crucial role in improving the population’s health. An article in BuiltIn highlighted various businesses leveraging big data to help healthcare organizations and researchers follow the trends to improve health conditions. For example, few companies help organize and integrate billions of records so that pharmaceutical companies can conduct better research for clinical trials, raise the level of safety, and get products to market faster.

Conclusion

Artificial Intelligence and Big data show promises of development in the healthcare industry, and several VC funding continues to flow into the sector every year. Healthcare organizations have learned to trust algorithms to use them, and there are several startups and firms dedicated and working relentlessly to help and improve the healthcare industry. To help contribute to this revolutionary division in world healthcare, AlmaBetter’s Full Stack Data Science program prepares you for any job role in Data Science, including positions in the healthcare sector.

Arpit Mehar
Content Developer Associate at AlmaBetter

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