AI is a mental ability used in solving -problems, learning the concepts and integrating functions, memory, attention, focus, planning and language. AI has greatly evolved over the past few years and the potential of benefits are huge.
AI Impact
Accenture predicts – AI health market will grow to an estimated $6.6 billion by 2021. The compound annual growth rate has increased to 40 per cent. 96 per cent of the hospitals in US have implemented a certified AI system
Accuracy of Database
Database plays an important role in the healthcare delivery process and AI is reducing the burden of managing health records. It can implement the proactive and predictive strategy while managing the patient data.
EMR has been a major step forward. It has promoted and galvanised the meaningful use of health information technology, which has resulted in a positive and notable shift from paper to computer-based health records.
Quality of Healthcare Delivery
Human intelligence is a product of years of learning and fine-tuning. Courtesy to cognitive skills and abilities he can perform multi-tasking, respond to new circumstances, providing patient-oriented care, adapt to a new environment and handle abstracts and complicated tasks.
AI being the replicated version of human intelligence requires several more R&D to respond to new circumstances, instructions and investments to beat human intelligence. With the help of AI and machine, clinicians can unearth the hidden patterns, trends, and correlations. However, once you teach the machines, they can perform far better than humans.
Clinical Productivity
Predictive models specifically trained on large amounts of data are more efficient in predicting patient outcomes though they lack human sense.
AI- Transforming medical care
While predicting the future of AI in medicine is not an easy task, it can certainly be said that it has a role to play in medicine as a partner. In combination with a human physician AI methods and systems can advance the delivery of care in a way that outperforms what either can do alone.
Step into the era of precision medicine which seeks to tailor medical treatment to the individual characteristics of a patient. This is likely to transform the delivery of medical care by enabling physicians to identify which genetic mutations drive certain cancers, and sequence our microbiome. Central to making precision medicine possible is AI which can make sense of massive amounts of clinical, genomic, and imaging data, thus helping to improve physician efficiency, increase diagnostic accuracy, and personalise treatment.
It can assist in assessing cancer risk. The clinician can pre-empt their patients with the results and chalk out a long-term plan of patient care. AI-based systems are poised to increase diagnostic efficiency in other areas of medicines as well. It will have a positive impact on radiology (CT, MRI and mammography interpretation), pathology (microscopic and cytological diagnoses) dermatology (lesion evaluation for potential melanoma). The field of pathology depends on the trained eye of the clinician to render a diagnosis of a bio-specimen. Given the many different types and subtypes of a disease and the avalanche of new data in the form of different biomarkers and genomics data, this is becoming an increasingly difficult task for the pathologist. The AI-based systems have the potential to augment clinical decision. One of the remarkable achievements is cognitive assisted robotics- da Vinci Surgical System.
Role of AI in breast cancer detection
Digital mammography has a sensitivity of 84 per cent for early BC detection. It can miss an early cancer or can have a false positive result. To safeguard, additional imaging in the form of double reading and more frequent screens are done which increases resource expenditure. AI can increase efficiency by using large complex datasets and image interpretation. It can overcome the inability of radiologists to decipher subtle changes on images.
It can combine these pixel-level variables and associations with patient clinical data, including any known patient risk factors, to develop predictive algorithms that may someday provide equal or better accuracy than human screening mammography. AI can provide clinical decision support to radiologists and improve the delivery of care and cost to patients.
Indian scenario
As of 2018 there were nearly 1.2 million new cancer cases diagnosed in a year in the country and this is expected to rise. India has only one oncologist for 1,600 patients, compared to one for 100 patients in the US, and hence faces an acute shortage of expertise.
Given the increasing number of cancer patients, fewer oncologists to treat them, the broad geographic footprint and the rapid increase in scientific and clinical knowledge about care, physicians in India face a challenging time in staying up-to-date about best practices in treatment and care management.
AI based systems IBM’s Watson can search through millions of pages of data, read countless medical articles, and far exceed the capacity of any human physician in its breadth and scale of knowledge. A study published by Manipal Hospitals in 2018, Watson for Oncology was concordant with the hospital’s MDT in 93 per cent of breast cancer treatment decisions (Somashekhar et al). IBM Watson agrees with the doctors only shows that it is competent in applying existing methods of care, not that it can improve them.
Assessing the Impact of AI on Physicians
AI replacing the clinicians
In terms of predictive analytics and image recognition, AI may soon become more effective than physicians, in handling millions of images in any reasonable time frame and interpreting even the most complex clinical images as accurately as today’s most experienced radiologists.
The doctor–patient relationship
AI – cannot engage in high-level conversation or interaction with patients to gain their trust, reassure them, or express empathy. Physicians are still needed for traditional physical exams, high-level patient-physician interaction, critical thinking and interpretation in ambiguous and challenging cases. AI-based systems are based on precedence and they can underperform in novel or unusual cases where there is no prior example to build on
Way forward
AI-based systems will support the skills of physicians and are unlikely to replace the traditional physician–patient relationship. AI will become a routine part of clinician’s daily lives, making their work more efficient, accurate, and valuable
Conclusions
AI will support the future needs of medicine by analysing the vast and various forms of data with a high level of accuracy. It would enhance clinical productivity due to its ability to handle a large capacity of tasks that are well suited for automation without any fatigue or burnout. It is likely to support and augment physicians by taking away the routine parts of a physician’s work, hopefully enabling the physician to spend more precious time with their patients, improving the human touch. AI is unlikely to replace physicians in the foreseeable future, maintaining human expertise in the interpretation of data and recommendations. It is incumbent on medical professionals to learn both the fundamentals of AI technology as well as how AI-based solutions can help them at work in providing better outcomes to their patients. Or the time may come; the physicians who use AI might replace physicians who are unable to do so.
Dr Kabir Rehmani,
Senior Consultant,
Surgical Oncology,
Fortis Hospital, Noida.
