Evidence map›Paper›PMID 38058345›Full record

ReviewCureus2023

Artificial Intelligence Applications for Biomedical Cancer Research: A Review.

Induni N Weerarathna, Aahash R Kamble, Anurag Luharia

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
7.3field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. 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

3 authors at 2 institutions in 1 country.

Induni N WeerarathnaBiomedical Sciences, School of Allied Health Sciences, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Aahash R KambleArtificial Intelligence and Data Science, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Anurag LuhariaRadiotherapy, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Jawaharlal Nehru Medical College · INDatta Meghe Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has rapidly evolved and demonstrated its potential in transforming biomedical cancer research, offering innovative solutions for cancer diagnosis, treatment, and overall patient care. Over the past two decades, AI has played a pivotal role in revolutionizing various facets of cancer clinical research. In this comprehensive review, we delve into the diverse applications of AI across the cancer care continuum, encompassing radiodiagnosis, radiotherapy, chemotherapy, immunotherapy, targeted therapy, surgery, and nanotechnology. AI has revolutionized cancer diagnosis, enabling early detection and precise characterization through advanced image analysis techniques. In radiodiagnosis, AI-driven algorithms enhance the accuracy of medical imaging, making it an invaluable tool for clinicians in the detection and assessment of cancer. AI has also revolutionized radiotherapy, facilitating precise tumor boundary delineation, optimizing treatment planning, and enabling real-time adjustments to improve therapeutic outcomes while minimizing collateral damage to healthy tissues. In chemotherapy, AI models have emerged as powerful tools for predicting patient responses to different treatment regimens, allowing for more personalized and effective strategies. In immunotherapy, AI analyzes genetic and imaging data to select ideal candidates for treatment and predict responses. Targeted therapy has seen great advancements with AI, aiding in the identification of specific molecular targets for tailored treatments. AI plays a vital role in surgery by offering real-time navigation and support, enhancing surgical precision. Moreover, the synergy between AI and nanotechnology promises the development of personalized nanomedicines, offering more efficient and targeted cancer treatments. While challenges related to data quality, interpretability, and ethical considerations persist, the future of AI in cancer research holds tremendous promise for improving patient outcomes through advanced and individualized care.

Indexed as

artificial intelligencecancer researchdiagnosticsnanotechnologypersonalized treatmentprecision medicineradiodiagnosis

Identifiers

PMID38058345
PMCPMC10697339
OpenAlexW4388377234

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.