How AI & Big Data are Transforming the Healthcare Processes

In the last 10 years, healthcare has been one of the fastest-growing sectors of the economy, i.e., the global economy as a whole. As pandemics like the “Coronavirus” and this recent “Monkeypox” outbreak continue to threaten, the industry is set to continue to grow. In an effort to stay competitive with the demand for healthcare services and solutions, organizations across the globe are turning towards new technologies, i.e., advanced ones like AI, machine learning, and Big Data.

Big data, machine learning (an application of AI), and artificial intelligence are used widely in healthcare processes. The benefits of big data, AI, and machine learning to healthcare are endless. The use of cognitive computing systems in radiological diagnostics, for instance, facilitates repetitive processes and creates sample analyses. Artificial intelligence and big data are helping the development of a new league of medical tools to predict when seriously ill patients will die and provide them with the best treatment, which includes correcting palliative care in good time to give them a dignified goodbye.

AI in Preventative Health Care

With the surmounting benefits of big data in healthcare, this new league of technologies such as AI and machine learning is evolving to be the key driving force for doctors’ decision-making for preventive healthcare that is more accurate and effective than ever before. AI can be applied to preventative health care in a variety of ways. Many other diseases and illnesses are being studied by researchers using AI as a predictor besides heart attacks. A few examples include:

• By analyzing mammograms and identifying hidden information that current clinicians cannot interpret, artificial intelligence may assist in predicting who will develop breast cancer within five years;
• Memory care clinics can use artificial intelligence to predict which patients will develop dementia within two years;
• In large data sets of patient data, artificial intelligence can help identify hidden patterns of correlation that could lead to early diabetes detection;
• Predicting acute kidney injuries before they actually occur.

The innovations around AI, machine learning labeling, and big data can be harnessed to overcome medical emergencies while assisting medical practitioners in managing intensive care operations. Big data has a significant role as everything here revolves around the data, i.e., the data in electronic health records (EHR), laboratory results, medication logs, and vital medical sign recordings. AI-powered healthcare systems and prediction models can aid doctors and the nursing care staff with data-driven alerts for better monitoring of their patients’ disease symptoms and diagnostic results, just to ensure them with a better path to recovery.

AI-Powered Robots for Healthcare

Manufacturing and warehousing are among the most common industries that use robots (the physical kind). Robots are also becoming more prevalent in hospitals, seeing their potential to leverage AI for automating healthcare processes, predicting possible healthcare outcomes, and assisting medical diagnostic and surgical procedures.

Robots can make a wide range of medical services more efficient and more effective. Robots are capable of providing surgeons with ‘superpowers,’ which are necessary for making precise and minimally invasive incisions, stitching wounds, and so forth.

AI-powered robotic systems can be used for a number of other applications. According to some medical experts, the future of high-precision surgery will depend on medical robots. These systems could improve postoperative rehabilitation and improve clinic logistical efficiency. Certainly, as technology like machine learning and artificial intelligence becomes more sophisticated, robots will play a larger role in medical treatment.

Leveraging the Potential of Big Data to Fight Cancer

Cancer is also being combated using big data technologies. The use of big data technologies can reveal hidden patterns in clinical data that can lead to earlier diagnosis of cancer, according to a National Geographic article. Cancer is life-threatening; however, detecting it at an early stage improves the chances of treating it. And big data and its applicability to AI medical diagnostic procedures can be significant to early cancer detection.

Genomic sequencing can reveal biomarkers for cancer and can also be used to identify groups that are particularly at risk, allowing new treatments to be discovered that have not been discovered before, thanks to big data technologies. The most progressive companies are using big data techniques to speed up their cancer analysis and develop more effective and faster treatments.

Big Data for Testing New Drugs in Clinical Trials

Conducting successful clinical trials is a challenge in drug development. Trends in Pharmacological Sciences reported that bringing a new — potentially life-saving — drug to market can take up to 15 years. Roughly half of that time is spent in clinical trials, many of which fail.

Artificial intelligence and big data technologies can, however, be used by researchers to identify the most suitable patients for clinical trials. Their medical responses can also be monitored more accurately and efficiently, saving them both time and money. Big data, Ai, and machine learning integration into the clinical trial process can help pharmaceutical facilities find the right prospects for the trial and play an assistive role in successful drug discovery with data sufficiency.

Final Thought

In addition to treating patients more effectively, AI, machine learning, and big data can improve healthcare quality by processing existing records, identifying symptoms, and analyzing outcomes simultaneously, enabling quicker and more effective prevention, diagnosis, and treatment. The healthcare facilities and medical practitioners will be better prepared to carry through their new emerging challenges around the healthcare system with the successful integration of AI and big data into their clinical operations