Evidence map›Paper›PMID 40699395›Full record

ReviewJournal of medical systems2025

Quantum Oncology: The Applications of Quantum Computing in Cancer Research.

Jiaran Li, Li Li, Ning Liu, Fuhao Xu, Tao Hu, Shuanghu Yuan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

6 authors.

Jiaran LiDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China.
Li LiDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China.
Ning LiuDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China.
Fuhao XuDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China.
Tao HuDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China.
Shuanghu YuanDepartment of Radiation Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, No.17 Lujiang Road, Hefei, 230001, Anhui, China. yuanshuanghu@sina.com.

Funding

National Natural Science Foundation of China NSFC82473235
6 · The paper itself

Abstract

A global technological race is underway to develop increasingly powerful and precise quantum computers. As a transformative computing paradigm, quantum computing offers the potential for exponentially accelerating specific algorithms, thereby providing the necessary computational power to process vast amounts of data. In light of the challenges classical computing faces with the complexity and volume of oncology data, we introduce the concept of "quantum oncology" and explore its potential applications throughout the cancer care continuum. Additionally, we address several challenges and potential solutions for integrating quantum computing into oncology research. By illuminating these issues, we aim to deepen the understanding of quantum computing's potential in oncology and advocate for multidisciplinary collaboration to propel the advancement of precision oncology. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Biomedical ResearchMedical OncologyNeoplasmsQuantum TheoryAlgorithmsHumansAnticancer drug developmentCancer detectionCancer diagnosisOncologyQuantum computingQuantum machine learningQuantum radiotherapy

Identifiers

PMID40699395

What OpenQuestion 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 OpenQuestion graph.