Evidence map›Paper›PMID 36739356›Full record

ReviewJournal of cancer research and clinical oncology2023

Artificial intelligence in pancreatic cancer: diagnosis, limitations, and the future prospects-a narrative review.

Maanya Rajasree Katta, Pavan Kumar Reddy Kalluru, Divyaraj Amber Bavishi, Maha Hameed, Sai Sudha Valisekka

Abstract readReview
In one paragraph

Review in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  2. Pancreatic cancer in 2025: Have we found a solution?World journal of gastroenterology · 2025
    Review
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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

5 authors.

Maanya Rajasree KattaGandhi Medical College, Hyderabad, India.
Pavan Kumar Reddy KalluruSri Venkateshwara Medical College, Tirupati, India.
Divyaraj Amber BavishiMedical College Baroda, Baroda, Gujarat, India.
Maha HameedClinical Research Department, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia. mwhameed2016@gmail.com.ORCID http://orcid.org/0000-0001-8066-4584
Sai Sudha ValisekkaSri Venkateshwara Medical College, Tirupati, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis review aims to explore the role of AI in the application of pancreatic cancer management and make recommendations to minimize the impact of the limitations to provide further benefits from AI use in the future.

methodsA comprehensive review of the literature was conducted using a combination of MeSH keywords, including "Artificial intelligence", "Pancreatic cancer", "Diagnosis", and "Limitations".

resultsThe beneficial implications of AI in the detection of biomarkers, diagnosis, and prognosis of pancreatic cancer have been explored. In addition, current drawbacks of AI use have been divided into subcategories encompassing statistical, training, and knowledge limitations; data handling, ethical and medicolegal aspects; and clinical integration and implementation.

conclusionArtificial intelligence (AI) refers to computational machine systems that accomplish a set of given tasks by imitating human intelligence in an exponential learning pattern. AI in gastrointestinal oncology has continued to provide significant advancements in the clinical, molecular, and radiological diagnosis and intervention techniques required to improve the prognosis of many gastrointestinal cancer types, particularly pancreatic cancer.

Indexed as

Pancreatic NeoplasmsArtificial IntelligenceHumansIntelligenceKnowledgeArtificial intelligenceGastrointestinal cancerLimitationsMachine learningPancreatic cancer

Identifiers

PMID36739356
PMCPMC11798185

What Socratic holds

Textmetadata
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.