Transformative Role of Artificial Intelligence in Reporting Haematology Cases: A Case Report

Artificial intelligence (AI) is transforming haematology reporting by improving accuracy, standardisation, and speed, addressing the need for timely and precise diagnostics. This study explores the use of the AI100 (SigTuple Technologies Private Limited, Bangalore, India) automated machine, a smart robotic microscope designed to automate the microscopic analysis of peripheral blood smears. Through the analysis of four haematology cases, this study demonstrates how AI technology facilitates efficient cell identification, enhances risk stratification, enables early detection of abnormalities, and accelerates diagnostic turnaround times. These advancements support pathologists in delivering improved patient care by augmenting traditional diagnostic methods. While AI can streamline processes and increase diagnostic accuracy, it is intended to complement, rather than replace, the expertise and judgement of skilled pathologists.

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Publication Details

Journal
Cureus
Published
2024-11-08
DOI
https://doi.org/10.7759/cureus.73274
Primary Topic
Digital Imaging for Blood Diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

Transformative Role of Artificial Intelligence in Reporting Haematology Cases: A Case Report

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Cureus
Digital Imaging for Blood Diseases
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Transformative Role of Artificial Intelligence in Reporting Haematology Cases: A Case Report

Neha Goel, Sanjeev Puri, Ankur Lath, Renu Ethirajan, Pradeep Garg, Pushkar D Admane
article en

Abstract

Artificial intelligence (AI) is transforming haematology reporting by improving accuracy, standardisation, and speed, addressing the need for timely and precise diagnostics. This study explores the use of the AI100 (SigTuple Technologies Private Limited, Bangalore, India) automated machine, a smart robotic microscope designed to automate the microscopic analysis of peripheral blood smears. Through the analysis of four haematology cases, this study demonstrates how AI technology facilitates efficient cell identification, enhances risk stratification, enables early detection of abnormalities, and accelerates diagnostic turnaround times. These advancements support pathologists in delivering improved patient care by augmenting traditional diagnostic methods. While AI can streamline processes and increase diagnostic accuracy, it is intended to complement, rather than replace, the expertise and judgement of skilled pathologists.

CureusVol. 16(11)
Horiba (Japan) (JP), Maharaja Krishna Chandra Gajapati Medical College and Hospital (IN), Ganesh Shankar Vidyarthi Memorial Medical College (IN), Sigma Technologies (United States) (US)
Openalex Percentile: Top 80%
Digital Imaging for Blood Diseases
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