bioRxiv / medRxiv
open access
CC BY-NC-ND 4.0
Deep Learning-Driven Pattern Analysis of Dried E. coli-Laden Urine Deposits for Point-of-Care Diagnostics
Urinary tract infections (UTIs) are a rising global health concern, primarily caused by Escherichia coli (E. coli), disproportionately affecting women and the elderly. Despite advancements in diagnostic techniques, critical gaps persist: time delays, high costs, and false-positive predictions. This
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Urinary NGF as A Biomarker for Acute Bacterial Cystitis#980268
- Bacterial Interference for Preventing Recurrent Urinary Tract Infection - New Ways of Treatment#1338464
- Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician#686443
- Diagnostic Tools in Patients With a Suspected Urinary Tract Infection in Primary Care#283064
- Detection of Biofilm Among Uropathogenic Escherichia Coli Clinical Isolates in Suez Canal University Hospitals#160384
Record · ID 1181778
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive