AI for Effective Diagnosis and Patient C

March 30th, 2021

AI-based health monitoring systems and digital health solutions are bringing some revolutionary changes to our healthcare industry by providing advanced healthcare solutions. Some new technologies and tools are helping to serve the patients better.


As we generate more and more patient data along with huge existing data, technology is taking over by helping us clear the clutter. AI can manage this massive data processing and help us with easy diagnosis and enhance the methods of treatment. Digital health, not only just stores data; it can even help to process the information and conclude the results.

How AI can Help in Diagnosis and Treatment

Diagnosis and treatment have been the main focus of AI since at least the 1970s. In those days, MYCIN was developed at Stanford for diagnosing blood-borne bacterial infections. They were only used as research tools and were never employed in clinical practice. But it initiated some revolutionary changes, and we see significant progress in how medicine is practiced now.


Recently IBM's Watson received considerable attention in the media for its focus on precision medicine, cancer diagnosis, and treatment. Still, the complexity of technology creates some barriers in the adaptation of these AI tools.


AI is helping physicians to improve treatment in several ways. With the help of AI, medication plans and follow-ups can be tailored efficiently based on individual needs. AI can process extensive data faster and more efficiently than humans.


Here are some ways AI can assist in diagnosis and treatment;

1. Detecting Diseases from Medical Imaging

Medical imaging provides much-needed diagnostic information, but it is dependent on human interpretation. It becomes challenging for specialists to meet the rapidly increasing need to evaluate medical images. Deep learning and AI can address this problem with automated diagnosis of medical images. Reports say deep learning models are matching and even exceeding humans in diagnostic performance. We can implement AI diagnostic tools in clinics to support a timely diagnosis.

2. Cancer Diagnosis

A cancer diagnosis has been relying heavily on manual processing. But in recent years, the use of digital trends and tools are accelerating. AI tools can help determine the urgency of the need for the treatment and what kind of resources might help. AI can automate specific diagnostic tasks, such as counting the cells or measuring things and automatically filling up the reports. With recent developments, AI is making its way in cancer screening and treatment recommendations also.

3. Patient Screening

Advising patients for any specific investigations such as CT, MRI, etc., depends on various symptoms as well as patient’s medical history in the records. Medical screening through specific characteristics can be identified by AI algorithms based on a large dataset. These algorithms can predict the risk factors and can further help in diagnosis.

4. Treatment

AI plays a significant role in developing new drugs, finding new ways to improve drug efficacy and drug interactions. Many healthcare start-ups are using AI for drug discovery and development. Besides helping in drug design, AI can aid in decision-making, define the right therapy for a patient, personalize the medications, record all the clinical data, and use it for future drug development.


Because of the increasing complexities of drug manufacturing processes and increasing demand for better and efficient product quality, AI technology is trying to confer human knowledge to machines, continuously improving drug manufacturing. In the past year, the synthesis and manufacture of sildenafil, diphenhydramine hydrochloride, and rufinamide have been done using a chemical programming language without any human intervention.

5. Patient Care

AI-based health monitoring systems can monitor a patient's health beyond hospital walls. These tools increase the efficiency of patient care by recording digital data, optimizing operational processes, and automating difficult tasks. Wearable devices and medical sensors have been found to be effective in managing the patient’s condition. The amalgamation of artificial intelligence (AI) with the healthcare system creates the new potential to improve patient safety outcomes. With intelligent decisions, AI is improving the quality of healthcare.


Through remote monitoring, AI empowers and educates patients to self-manage their condition, which reduces frequent hospitalization and improves patients’ quality of life. During the pandemic, remote monitoring has helped health professionals manage patients’ needs without risking the spread of infection.

How Reliable is AI Diagnostics?

Deep learning performance in diagnosis was evaluated and a review has been published by The Lancet Digital Health. According to its analysis, AI can diagnose a disease with 87% efficiency, whereas health professionals yield 86% efficiency. Deep learning technology and AI achieve equivalent levels of diagnostic accuracy as that of health-care professionals.


AI techniques are also contributing to the prediction of breast cancer recurrence and prioritizing the importance of prognosis. According to the Journal of the National Cancer Institute, the AI can do cancer detection comparable to an average breast radiologist in this retrospective set with around 95% accuracy. Their performance is comparable to any medical expert.


AI has the ability to learn and analyze diseases and conditions quickly. With tremendous progress, we are expecting more accurate and faster diagnoses and better treatment options in the future.

Why we Need AI for Diagnosis

Manual diagnostic errors by health care professionals are a global challenge. A recent study stated that about 5% of patients in the US experience diagnostic errors every year. AI can evaluate extensive data to give a more accurate, error-free diagnosis.


Also, AI can help to overcome the need for more health experts and an increased workload on doctors. Healthcare accessibility to everyone is essential. Many remote places don’t get the needed medical care. AI can make healthcare more accessible and affordable to everyone.


Digital healthcare solutions can help doctors process a vast amount of health data, thus improving their decision-making process. AI-based health monitoring systems give a comprehensive approach to disease management. AI can simplify the diagnosis as well as the treatment process.

Bottom Line

Artificial Intelligence (AI) is a promising field of the healthcare industry, which is rapidly changing the way we provide medical care. The latest advancements in artificial intelligence and machine learning are building healthcare software solutions for better health management for everyone. Fast diagnosis and customized treatments are improving patient’s quality of life. Moving forward with these technologies, we can say, “AI is for better health.”