Evidence map›Paper›PMID 36980603›Full record

ArticleCancers2023

Hyperthermia Treatment Monitoring via Deep Learning Enhanced Microwave Imaging: A Numerical Assessment.

Álvaro Yago Ruiz, Marta Cavagnaro, Lorenzo Crocco

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In one paragraph

Article in Cancers, 2023. 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. 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

3 authors.

Álvaro Yago RuizCNR-IREA National Research Council of Italy, Institute for Electromagnetic Sensing of the Environment, 80124 Naples, Italy.ORCID 0000-0001-9390-9368
Marta CavagnaroDepartment of Information Engineering, Electronics, and Telecommunications, University of Rome "La Sapienza", 00184 Rome, Italy.ORCID 0000-0002-7624-1113
Lorenzo CroccoCNR-IREA National Research Council of Italy, Institute for Electromagnetic Sensing of the Environment, 80124 Naples, Italy.ORCID 0000-0003-2498-3219

Funding

European Union 764479
6 · The paper itself

Abstract

The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation.

Indexed as

deep learninghyperthermia treatmentmicrowave imagingtemperature monitoring

Identifiers

PMID36980603
PMCPMC10046415

What OpenQuestion holds

Textfull text, public
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measurements read13
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.