Evidence map›Paper›PMID 39943530›Full record

ReviewSensors (Basel, Switzerland)2025

Artificial Intelligence in IR Thermal Imaging and Sensing for Medical Applications.

Antoni Z Nowakowski, Mariusz Kaczmarek

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
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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

2 authors.

Antoni Z NowakowskiBiomedical Engineering Department, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland.
Mariusz KaczmarekBiomedical Engineering Department, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland.ORCID 0000-0001-6488-7489

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The state of the art in IR thermal imaging methods for applications in medical diagnostics is discussed. A review of advances in IR thermal imaging technology in the years 1960-2024 is presented. Recently used artificial intelligence (AI) methods in the analysis of thermal images are the main interest. IR thermography is discussed in view of novel applications of machine learning methods for improved diagnostic analysis and medical treatment. The AI approach aims to improve image quality by denoising thermal images, using applications of AI super-resolution algorithms, removing artifacts, object detection, face and characteristic features localization, complex matching of diagnostic symptoms, etc.

Indexed as

Artificial IntelligenceThermographyAlgorithmsHumansImage Processing, Computer-AssistedInfrared RaysMachine Learningartificial intelligence methodsIR thermal imagingmachine learningmedical thermography

Identifiers

PMID39943530
PMCPMC11820461

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.