Artificial intelligence in haematology laboratory diagnosis: Current applications, challenges, and future directions
Hussam A. Osman · 2026
Read Artificial intelligence in haematology laboratory diagnosis: Current applications, challenges, and future directions by Hussam A. Osman (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13443926.txt.
Description
Hussam Osman reviews smart computer tools in blood lab diagnosis in a 2026 paper. Blood work leans on hand scope reads and expert eyes, which vary between labs and tire with load. The review sweeps four databases for tools that read cell shapes, flow data, chromosome maps, and gene marks.
Deep learning nets scored well at cell shape reads, from blood smears to marrow slides, and caught faint odd marks. Flow tools sped gate work and flagged rare events. Gene tools aided chromosome sorts and variant calls, while triage tools helped plan care steps. Blocks span messy data, thin proof, cost, and rule gaps, with African labs in sharp focus. The author urges shared data and staged proof before wide trust.
Catalog record
| CREATOR | Hussam A. Osman |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 28941 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |