Tackling Malaria Diagnosis in sub-Saharan Africa with Fast, Accurate and Scalable Robotic Automation, Computer Vision and Machine Learning (FASt-Mal)

通过快速、准确和可扩展的机器人自动化、计算机视觉和机器学习 (FASt-Mal) 解决撒哈拉以南非洲地区的疟疾诊断问题

• 批准号: EP/P028608/1
• 负责人: Delmiro Fernandez-Reyes
• 金额: $ 169.53万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP028608%2F1
• 关键词: Tackling; Malaria; Diagnosis; sub; Saharan

Malaria affect about 300 million people worldwide leading to around one million deaths each year. Up to eighty-five percent of the cases occur in sub-Saharan Africa with about 90% mortality in the under five years-of-age group due to severe malaria syndromes. Control of malaria remains a major public health issue in sub-Saharan Africa developing countries. A quarter of the global malaria cases and a third of malaria-attributable childhood deaths occur in the most populous country of Africa, Nigeria (160M inhabitants) and indicates the importance of the problem. Accurate malaria diagnosis relies on the recognition of clinical parameters and more importantly in the microscopic detection of malarial parasites, parasitised red-blood-cells in peripheral-blood films. Malaria parasite detection and counting by human-operated optical microscopy is the current "gold standard" and despite its major severe drawbacks, other non-microscopic methodologies have not been able to outperform it. Presumptive treatment for malaria (without microscopic confirmation) is wasteful of drugs and ineffective if the diagnosis was wrong, a drain on often precious health resources, fuels antimalarial resistance and have made control and elimination interventions unachievable. We aim to create and test in real-world conditions a fast, accurate and scalable malaria diagnosis system by replacing human-expert optical-microscopy with a robotic automated computer-expert system FASt-MalPrototype that assesses similar digital-optical-microscopy representations of the problem. The system aims to provide access to effective malaria diagnosis, a challenge that is faced by all developing countries where malaria is endemic.

疟疾影响着全球约3亿人，每年导致约100万人死亡。高达85%的病例发生在撒哈拉以南非洲，其中约90%的5岁以下儿童死于严重的疟疾综合征。控制疟疾仍然是撒哈拉以南非洲发展中国家的一个主要公共卫生问题。全球四分之一的疟疾病例和三分之一的疟疾导致的儿童死亡发生在非洲人口最多的国家尼日利亚（1.6亿居民），这表明了这一问题的重要性。准确的疟疾诊断依赖于对临床参数的识别，更重要的是在显微镜下检测疟疾寄生虫，寄生在外周血膜中的红细胞。通过人工操作的光学显微镜检测和计数疟疾寄生虫是目前的“金标准”，尽管它存在严重的缺陷，但其他非显微镜方法还无法超越它。对疟疾的推定治疗（未经显微镜确认）是对药物的浪费，如果诊断错误则无效，消耗往往宝贵的卫生资源，助长抗疟药耐药性，并使控制和消除干预措施无法实现。我们的目标是创建和测试一个快速、准确和可扩展的疟疾诊断系统，用一个机器人自动化计算机专家系统fast - malprototype取代人类专家光学显微镜，以评估类似的数字光学显微镜问题的表现。该系统旨在提供有效的疟疾诊断，这是疟疾流行的所有发展中国家面临的一项挑战。

项目成果

Depleted circulatory complement-lysis inhibitor (CLI) in childhood cerebral malaria returns to normal with convalescence.

儿童脑型疟疾中耗尽的循环补体裂解抑制剂（CLI）会随着康复期恢复正常。

• DOI: 10.1186/s12936-020-03241-5
• 发表时间: 2020
• 期刊: Malaria journal
• 影响因子: 3
• 作者: Abah SE

Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa.

• DOI: 10.1038/s41598-020-72575-6
• 发表时间: 2020-09-28
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Brown BJ;Manescu P;Przybylski AA;Caccioli F;Oyinloye G;Elmi M;Shaw MJ;Pawar V;Claveau R;Shawe-Taylor J;Srinivasan MA;Afolabi NK;Rees G;Orimadegun AE;Ajetunmobi WA;Akinkunmi F;Kowobari O;Osinusi K;Akinbami FO;Omokhodion S;Shokunbi WA;Lagunju I;Sodeinde O;Fernandez-Reyes D
• 通讯作者: Fernandez-Reyes D

Low plasma haptoglobin is a risk factor for life-threatening childhood severe malarial anemia and not an exclusive consequence of hemolysis.

• DOI: 10.1038/s41598-018-35944-w
• 发表时间: 2018-12-03
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Abah SE;Burté F;Marquet S;Brown BJ;Akinkunmi F;Oyinloye G;Afolabi NK;Omokhodion S;Lagunju I;Shokunbi WA;Wahlgren M;Dessein H;Argiro L;Dessein AJ;Noyvert B;Hunt L;Elgar G;Sodeinde O;Holder AA;Fernandez-Reyes D
• 通讯作者: Fernandez-Reyes D

Specialist hybrid models with asymmetric training for malaria prevalence prediction.

• DOI: 10.3389/fpubh.2023.1207624
• 发表时间: 2023
• 期刊: FRONTIERS IN PUBLIC HEALTH
• 影响因子: 5.2
• 作者: Fisher, Thomas;Rojas-Galeano, Sergio;Fernandez-Reyes, Delmiro
• 通讯作者: Fernandez-Reyes, Delmiro

Content aware multi-focus image fusion for high-magnification blood film microscopy.

• DOI: 10.1364/boe.448280
• 发表时间: 2022-02-01
• 期刊: Biomedical optics express
• 影响因子: 3.4
• 作者: Manescu P;Shaw M;Zajiczek LN;Bendkowski C;Claveau R;Elmi M;Brown BJ;Fernandez-Reyes D
• 通讯作者: Fernandez-Reyes D