ArticlePeerJ2022
Automatic detection of the parasite
Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 34 citations in OpenAlex.
- Advances and Challenges in the Diagnosis of Vector-Borne Protozoal Infections in Veterinary Medicine.Pathogens (Basel, Switzerland) · 2026Review
- Artificial intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using smartphone microscopy.PLoS neglected tropical diseases · 2026Article
- Artificial intelligence-powered microscopy: Transforming the landscape of parasitology.Journal of microscopy · 2026Review
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Pathogenic Significance of Trypanosomatids: Progress in Drug Resistance, Control Strategies, and Artificial Intelligence.Interdisciplinary perspectives on infectious diseases · 2026Review
- Automated identification of spotted-fever tick vectors using convolutional neural networks.Medical and veterinary entomology · 2025Article
- From Detection to Motion-Based Classification: A Two-Stage Approach forJournal of imaging · 2025Article
- Classification of Trypanosoma brucei mammalian life cycle stages using Deep Learning Algorithms.PLoS neglected tropical diseases · 2025Article
- YOLO-Tryppa: A Novel YOLO-Based Approach for Rapid and Accurate Detection of Small Trypanosoma Parasites.Journal of imaging · 2025Article
- Weighted-VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infection.PloS one · 2025Article
- Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models.Sensors (Basel, Switzerland) · 2024Article
- Article
- Edge Artificial Intelligence (AI) for real-time automatic quantification of filariasis in mobile microscopy.PLoS neglected tropical diseases · 2024Article
- Trajectory-driven computational analysis for element characterization in Trypanosoma cruzi video microscopy.PloS one · 2024Article
- Development of a low-cost robotized 3D-prototype for automated optical microscopy diagnosis: An open-source system.PloS one · 2024Article
- Assessment of Deep Learning Models for Cutaneous Leishmania Parasite Diagnosis Using Microscopic Images.Diagnostics (Basel, Switzerland) · 2023Article
- Tryp: a dataset of microscopy images of unstained thick blood smears for trypanosome detection.Scientific data · 2023Article
- Image dataset of urine test results on petri dishes for deep learning classification.Data in brief · 2023Article
- Predicting medical device failure: a promise to reduce healthcare facilities cost through smart healthcare management.PeerJ. Computer science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chagas disease is a life-threatening illness caused by the parasite
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.