# An AI based, open access screening tool for early diagnosis of Burkitt lymphoma

## TL;DR

This paper introduces an open-access AI tool to help diagnose Burkitt lymphoma quickly in regions with limited pathology resources.

## Contribution

A novel AI-based screening tool for Burkitt lymphoma using multiple image magnifications and ensemble methods for accessible, efficient diagnosis.

## Key findings

- The AI tool achieved robust performance using an ensemble-based consensus approach and multiple image magnifications.
- The model was trained on 90 BL patient slides and 70 control samples, demonstrating effectiveness with a relatively small dataset.
- The open-access tool enables remote clinics to screen slides using low-cost scanners, improving timely diagnosis.

## Abstract

Burkitt Lymphoma (BL) is a highly treatable cancer. However, delayed diagnosis of BL contributes to high mortality in BL endemic regions of Africa. Lack of enough pathologists in the region is a major reason for delayed diagnosis. The work described in this paper is a proof-of-concept study to develop a targeted, open access AI tool for screening of histopathology slides in suspected BL cases. Slides were obtained from a total of 90 BL patients. 70 Tonsillectomy samples were used as controls. We fine-tuned 6 pre-trained models and evaluated the performance of all 6 models across different configurations. An ensemble-based consensus approach ensured a balanced and robust classification. The tool applies novel features to BL diagnosis including use of multiple image magnifications, thus enabling use of different magnifications of images based on the microscope/scanner available in remote clinics, composite scoring of multiple models and utilizing MIL with weak labeling and image augmentation, enabling use of relatively low sample size to achieve good performance on the inference set. The open access model allows free access to the AI tool from anywhere with an internet connection. The ultimate aim of this work is making pathology services accessible, efficient and timely in remote clinics in regions where BL is endemic. New generation of low-cost slide scanners/microscopes is expected to make slide images available immediately for the AI tool for screening and thus accelerate diagnosis by pathologists available locally or online.