Home ›
Entities
› academia
› A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images
A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images
Research article (Neural Computing and Applications, 2024) · cited 18× · AI/ML
A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images
Summary
A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images is a scholarly article[1].
Key Facts
A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-new-deep-neuro-fuzzy-system-for-lyme-disease-detection-and-classification-using-unet-inception-and-xgboost-model-from-
MLA“A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-new-deep-neuro-fuzzy-system-for-lyme-disease-detection-and-classification-using-unet-inception-and-xgboost-model-from-.
BibTeX@misc{4ortxyz_a-new-deep-neuro-fuzzy-system-for-lyme-disease-detection-and-classification-using-unet-inception-and-xgboost-model-from-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images}}, year = {2026}, url = {https://4ort.xyz/entity/a-new-deep-neuro-fuzzy-system-for-lyme-disease-detection-and-classification-using-unet-inception-and-xgboost-model-from-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A new deep neuro-fuzzy system for Lyme disease detection and classification using UNet, Inception, and XGBoost model from medical images — https://4ort.xyz/entity/a-new-deep-neuro-fuzzy-system-for-lyme-disease-detection-and-classification-using-unet-inception-and-xgboost-model-from- (retrieved 2026-05-24)
