Evidence map›Paper›PMID 40033507›Full record

ReviewCurrent pharmaceutical design2026

Leveraging AI and Natural Compounds: Innovative Approaches in the Diagnosis and Treatment of Hepatocellular Carcinoma.

Mohd Suhail, Mohammad Tarique, Shams Tabrez, Darshan Badal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pharmaceutical design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Mohd SuhailKing Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.ORCID 0000-0002-1641-4633
Mohammad TariqueDepartment of Child Health, School of Medicine, University of Missouri, Columbia, Missouri, 65201, USA.
Shams TabrezKing Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Darshan BadalDepartment of Child Health, School of Medicine, University of Missouri, Columbia, Missouri, 65201, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver cancer, particularly hepatocellular carcinoma (HCC), remains a significant global health challenge owing to its high incidence and position as the fourth leading cause of cancer-related mortality. HCC represents 75-85% of all liver cancer cases and ranks as the sixth most prevalent cancer globally. Several factors, including late-stage diagnosis, limited treatment effectiveness, resistance to conventional therapies, and adverse side effects, hinder the delivery of life-prolonging care to patients with HCC. Current treatment options such as chemotherapy, immunotherapy, and adjuvant therapy are often associated with severe side effects. Consequently, there is an urgent need for improved diagnostic methods and alternative therapeutic approaches to extend life expectancy and reduce HCC-related mortalities. Artificial Intelligence (AI) is an emerging technology that offers promising advances for the early detection of HCC. In terms of alternative treatments, natural compounds have garnered significant attention because of their diverse biological activities, such as antitumor, antiviral, antimicrobial, antioxidant, anti-inflammatory, hepatoprotective, antimutagenic, and cardioprotective effects, and their relatively lower side effect profiles. These compounds exhibit hepatoprotective properties by modulating key molecular pathways involved in HCC development and progression. This article provides an overview of recent advances in the understanding of liver cancer etiology, therapeutic targets in HCC pathogenesis, the role of AI in its detection, and the potential of natural products, particularly flavonoids, as preventive and therapeutic agents against HCC, highlighting their underlying mechanisms of action.

Indexed as

Antineoplastic AgentsArtificial IntelligenceBiological ProductsCarcinoma, HepatocellularLiver NeoplasmsAnimalsHumansAntineoplastic AgentsBiological Productsantimutagenicartificial intelligence (AI)hepatocellular carcinoma (HCC)liver cancerNatural compoundsphytochemicals

Identifiers

PMID40033507

What OpenQuestion holds

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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 OpenQuestion graph.