Evidence map›Paper›PMID 39072365›Full record

ReviewOncology2025

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

Meghna Birla, Rajan, Prabhat Gautam Roy, Ishaan Gupta, Prabhat Singh Malik

Abstract readReview
In one paragraph

Review in Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Meghna BirlaDepartment of Medical Oncology, DR. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
RajanIndian Institute of Technology (IIT), Delhi, India.
Prabhat Gautam RoyDepartment of Medical Oncology, DR. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Ishaan GuptaIndian Institute of Technology (IIT), Delhi, India.
Prabhat Singh MalikDepartment of Medical Oncology, DR. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences (AIIMS), New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical decision-making in oncology is a complex process influenced by numerous disease-related factors, patient demographics, and logistical considerations. With the advent of artificial intelligence (AI), precision medicine is undergoing a shift toward more precise and personalized care. Wearable device technology complements this paradigm shift by offering continuous monitoring of patient vitals, facilitating early intervention, and improving treatment adherence. The integration of these technologies promises to enhance the quality of oncological care, making it more responsive and tailored to individual patient needs, thereby enabling wider implementation of such applications in the clinical setting. SUMMARY: This review article addresses the integration of wearable devices and AI in oncology, exploring their role in patient monitoring, treatment optimization, and research advancement along with an overview of completed clinical trials and utility in different aspects. The vast applications have been exemplified using several studies, and all the clinical trials completed till date have been summarized in Table 2. Additionally, we discuss challenges in implementation, regulatory considerations, and future perspectives for leveraging these technologies to enhance cancer care and radically changing the global health sector. KEY MESSAGES: AI is transforming cancer care by enhancing diagnostic, prognostic, and treatment planning tools, thus making precision medicine more effective. Wearable technology facilitates continuous, noninvasive monitoring, improving patient engagement and adherence to treatment protocols. The combined use of AI and wearables aids in monitoring patient activity, assessing frailty, predicting chemotherapy tolerance, detecting biomarkers, and managing treatment adherence. Despite these advancements, challenges such as data security, privacy, and the need for standardized devices persist. In the foreseeable future, wearable technology can hold significant potential to revolutionize personalized oncology care, empowering clinicians to deliver comprehensive and tailored treatments alongside standard therapy.

Indexed as

Artificial IntelligenceClinical Decision-MakingMedical OncologyNeoplasmsWearable Electronic DevicesHumansPrecision MedicineArtificial intelligence in medicineDecision-makingOncologyPrecision medicineWearable technology

Identifiers

PMID39072365
PMCPMC11731833

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.