However, an effective solution has now come into being to transform this bleak story: Artificial Intelligence in healthcare. The power of AI in cancer detection to process big volumes of data, find the slightest patterns that a human eye will not see, and learn from each case that it processes presents a new dawn in cancer detection early in life, which brings hope, speed, and precision to the optimum.

The Rationale of Early Detection

When a disease is identified early, the treatment becomes much better and easily accessible. The World Health Organisation reported that a 70-90% survival rate can be achieved when the cancer is caught at its initial stage, unlike the situation when the cancer is already advanced, where the percentage of survival rate is less than 30%. However, conventional screening procedures sometimes require professionals to interpret, may take longer and even fail to reach people, especially in rural and semi-urban areas in India.

This is where AI-powered diagnostic tools for AI in cancer detection come in and allow clinicians to screen quickly, with higher precision, and even remote screening abilities are possible. Whether in the scanning of radiology images or the decoding of genomic pathology, or the identification of risky markers on a genetic basis, artificial intelligence in healthcare is automating a process once manual and tedious.

How Artificial Intelligence (AI) is Altering Proactive Cancer Detection?

1.  Deep Learning in Imaging

AI in cancer detection is currently analysing medical imaging, such as X-rays, mammograms, CT scans and MRIs, with amazing accuracy. Deep learning algorithms can be used in the development of tools capable of identifying anomalies like lung nodules or breast masses much earlier than conventional radiology equipment. To take an example, an AI model designed by Google Health to detect breast cancer recorded higher performance than radiologists because the former had lower false positive and false negative rates.

At a more local level, artificial intelligence in healthcare models, such as those created by Tata Memorial Centre and startups, such as Niramai, have ensured that breast cancer can be screened without being invasive, requires no screening costs, and is accessible, particularly to Indian women who are not willing to undergo a mammogram. Thermalytix technology of Niramai is non-radiation and can be utilised even in rural settings since it is based on thermal imaging with the aid of AI in cancer treatment to identify tumours.

2.  AI-Assisted Pathology

Thousands of digital pathology slides can be scanned and interpreted in seconds by artificial intelligence in healthcare, and cancer cells are detected using their shape, structure, and genetic activity. Not only does this also make the diagnosis faster as well but it also decreases human error. Solutions utilising AI in cancer detection, such as AI100 created by SigTuple, are already implemented in the pathology labs in India to process blood and tissue samples. Through such platforms, it is possible to overcome the shortage of trained pathologists in the lower-level cities, notably tier 2 and 3 cities.

3.  High-Risk Group Predictive Analytics

It is also possible to use AI in cancer treatment to analyse the patient data, including genetics, lifestyle, and previous medical history, to predict the probability of cancer and assist with the personalised approach to the strategy of screening. To give an example, a person with a family history of breast cancer may have the AI in cancer detection generated alerts on the earlier and more frequent screenings. An example of how machine learning may be applied to prevent a disease was illustrated by a study by IBM Watson, which showed that it is possible, with enough evidence of patterns in a patient record, to find that they are at a high risk of developing colorectal cancer several years before they develop any symptoms.

4.  Medical Record Natural Language Processing (NLP)

Using NLP algorithms based on artificial intelligence in healthcare, it is possible to get through patient records, clinician notes, and pathology reports to identify the presence of useful information and raise an alarm on the endangered and those requiring further checks. This minimises delays, and there can be no case which goes without a case. Hospitals in India, such as AIIMS, are conducting experiments with AI in cancer detection tools to digitise and analyse patient records in order to better monitor cancer.

The Indian Healthcare System

The public health system in India is overburdened with a ratio of 1 doctor to 834 patients, and often, the rural areas have deficient access to specialists. Artificial Intelligence in healthcare should be able to decentralise cancer screening by introducing powerful diagnosis tools to primary health centres, mobile vans and smartphones.

States are deploying AI in cancer treatment devices on the move; Karnataka and Tamil Nadu have been using the handsets to screen against oral cancer and cervical cancer. Such mobile devices will enable ASHA workers and community health personnel to screen the patients directly in the field, and the results can be reviewed by the oncologists remotely. Furthermore, the Digital India Project and the Ayushman Bharat Digital Mission are establishing the needed infrastructure of data that would facilitate the massive implementation of artificial intelligence in healthcare.

Challenges of Adopting AI in Healthcare Systems

There has been enormous potential with AI in cancer detection, but it is not without its problems or consequences. Adoption can be hindered by data privacy and security breaches, data availability with regard to having high-quality training sets available, language factors in medical NLP, and regulatory approvals.

Besides, AI in cancer treatment is an instrument rather than human knowledge. The doctors and health workers should be trained on how to make optimum use of these tools. India, too, requires such public-private partnerships to ramp up these technologies to low-income and remote populations where the burden of cancer is increasing, but there is still little awareness and little access.  This is where the expertise of established medical institutions, such as the Department of Medicine at Sir Ganga Ram Hospital, becomes vital in translating AI-driven insights into sound clinical decisions.

The process of applying Artificial Intelligence in healthcare for the early diagnosis of cancer is not science fiction, as it is actual and already saves human lives. In the case of a nation such as India, whose fight against cancer is concerned as much with access and awareness as it is with technology, AI in cancer detection presents an effective solution for the future. Whether the AI in cancer treatment is in rural or urban healthcare systems, whether it is screening a woman in the breast or in the cervix in the rural clinics or the sophisticated smart diagnosis in urban hospitals, it is changing the tide, and, at that, in a rather silent yet strong way. In the words of one of the specialists at Tata Memorial Centre: "And with AI, it is not just early detection of cancer but a second chance of life."