Evidence map›Paper›PMID 40103737›Full record

ReviewFrontiers in digital health2025

Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation.

Isha Goel, Yogendra Bhaskar, Nand Kumar, Sunil Singh, Mohammed Amanullah, Ruby Dhar, Subhradip Karmakar

Abstract readReview
In one paragraph

Review in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Article
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  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Isha GoelDepartment of Biochemistry, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Yogendra BhaskarICMR Computational Genomics Centre, Indian Council of Medical Research (ICMR), New Delhi, India.
Nand KumarDepartment of Psychiatry, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Sunil SinghDepartment of Biochemistry, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Mohammed AmanullahDepartment of Clinical Biochemistry, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Ruby DharDepartment of Biochemistry, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Subhradip KarmakarDepartment of Biochemistry, All India Institute of Medical Sciences (AIIMS), New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early diagnosis and accurate prognosis play a pivotal role in the clinical management of cancer and in preventing cancer-related mortalities. The burgeoning population of Asia in general and South Asian countries like India in particular pose significant challenges to the healthcare system. Regrettably, the demand for healthcare services in India far exceeds the available resources, resulting in overcrowded hospitals, prolonged wait times, and inadequate facilities. The scarcity of trained manpower in rural settings, lack of awareness and low penetrance of screening programs further compounded the problem. Artificial Intelligence (AI), driven by advancements in machine learning, deep learning, and natural language processing, can profoundly transform the underlying shortcomings in the healthcare industry, more for populous nations like India. With about 1.4 million cancer cases reported annually and 0.9 million deaths, India has a significant cancer burden that surpassed several nations. Further, India's diverse and large ethnic population is a data goldmine for healthcare research. Under these circumstances, AI-assisted technology, coupled with digital health solutions, could support effective oncology care and reduce the economic burden of GDP loss in terms of years of potential productive life lost (YPPLL) due to India's stupendous cancer burden. This review explores different aspects of cancer management, such as prevention, diagnosis, precision treatment, prognosis, and drug discovery, where AI has demonstrated promising clinical results. By harnessing the capabilities of AI in oncology research, healthcare professionals can enhance their ability to diagnose cancers at earlier stages, leading to more effective treatments and improved patient outcomes. With continued research and development, AI and digital health can play a transformative role in mitigating the challenges posed by the growing population and advancing the fight against cancer in India. Moreover, AI-driven technologies can assist in tailoring personalized treatment plans, optimizing therapeutic strategies, and supporting oncologists in making well-informed decisions. However, it is essential to ensure responsible implementation and address potential ethical and privacy concerns associated with using AI in healthcare.

Indexed as

artificial intelligencecancer managementdeveloping nationdigital healthpersonalized medicine

Identifiers

PMID40103737
PMCPMC11913822

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.