Evidence map›Paper›PMID 42832322›Full record

ArticleClinical journal of oncology nursing2026

Leveraging Artificial Intelligence to Monitor Patients With Prostate Cancer in a Retrospective Cohort of Radiation Oncology Clinic Patients.

Richard Nishan Boyajian, Molly Hagen, Sugato Bagchi, Shilpa Mahatma, Ashleigh Kowtoniuk, Quoc-Dien Trinh, Tarun Kumar, Paul L Nguyen

Abstract read
In one paragraph

Article in Clinical journal of oncology nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Richard Nishan BoyajianRichard Nishan Boyajian.
Molly HagenMolly Hagen.
Sugato BagchiSugato Bagchi.
Shilpa MahatmaShilpa Mahatma.
Ashleigh KowtoniukAshleigh Kowtoniuk.
Quoc-Dien TrinhQuoc-Dien Trinh.
Tarun KumarTarun Kumar.
Paul L NguyenPaul L. Nguyen.

Funding

VIPCare: Virtual Predictive Care workflow with EHR integrated surveillance for optimalfollow-up care management for Cancer PatientsR44CA281547 · NCI · VIZLITICS INC. · PI Tarun Kumar · 2025 to 2026
$2.3M
VIPCare: Virtual Predictive Care workflow with integrated surveillance for optimal care protocol selection and management in at-risk prostate cancer patientsR43CA281547 · NCI · VIZLITICS INC. · PI HENSLEY ALFORD, SHARON · 2023 to 2024
$462k
NCI NIH HHS R43 CA281547NCI NIH HHS R44 CA281547
6 · The paper itself

Abstract

backgroundThe U.S. oncology workforce is not increasing at the same pace as the cancer survivor population. Cancer care requires extended coordination across multiple disciplines. Oncology teams need technological solutions to support patient surveillance and meet growing care demands.

objectivesThe purpose of this study was to develop and test an artificial intelligence (AI) approach to identify and track care states in patients with prostate cancer.

methodsThe study examined data from a retrospective cohort of 180 patients to develop ground truth care state assignments with parameters set by clinicians, then developed an AI model that set its own parameters for care state assignment and tested it on this cohort dataset. The study assessed the agreement between assignments made by the AI model and clinician specialists.

findingsThe AI model produced care state assignments for all 180 patients in less than one second, and agreement with the clinician-assigned care state was 95%.

Indexed as

Artificial IntelligenceProstatic NeoplasmsRadiation OncologyAgedAged, 80 and overCohort StudiesHumansMaleMiddle AgedRetrospective StudiesUnited Statesartificial intelligenceelectronic health recordpatient managementprostate cancer

Identifiers

PMID42832322
PMCPMC13649037

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.