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NiADA(无创贫血检测应用程序),一款基于智能手机并借助人工智能实时测量血红蛋白的应用程序:一项临床验证。

NiADA (Non-invasive Anemia Detection App), a Smartphone-Based Application With Artificial Intelligence to Measure Blood Hemoglobin in Real-Time: A Clinical Validation.

作者信息

Das Semanti, Ahamed Farhad, Das Aditi, Das Debjeet, Nandi Jhuma, Banerjee Krishanu

机构信息

Community Medicine, All India Institute of Medical Sciences, Kalyani, Kalyani, IND.

Community Medicine and Family Medicine, All India Institute of Medical Sciences, Kalyani, Kalyani, IND.

出版信息

Cureus. 2024 Jul 26;16(7):e65442. doi: 10.7759/cureus.65442. eCollection 2024 Jul.

Abstract

Background  Anemia is a severe public health problem in India affecting more than half of the population. To reduce its burden on the population, the Government of India under the Anemia Mukt Bharat program has adopted a monitoring strategy for the diagnosis and treatment of anemia. Point-of-care testing (POCT) devices play a pivotal role in testing hemoglobin at a community level where sophisticated laboratory instruments are not available. The majority of the currently available POCT devices are invasive in nature which have their own limitations. A non-invasive method of hemoglobin estimation will address many of the limitations of an invasive POCT instrument, which will further improve people's acceptability for hemoglobin testing. The Non-Invasive Anemia Detection App (NiADA) (Monere AI Private Limited, Kolkata, West Bengal, India, a non-invasive POCT application, uses artificial intelligence (AI) to predict the hemoglobin level from lower eyelid images. This real-time, point-of-care, low-cost solution uses a custom computer vision deep-learning algorithm to determine blood hemoglobin value.  Method  The study validates an AI-based smartphone application NiADA against laboratory hemoglobin estimation and a widely used point-of-care hemoglobin estimation instrument (HemoCue Hb 301; HemoCue AB, Angelholm, Skane County, Sweden). The study was conducted in a tertiary care hospital in Eastern India and recruited a total of 556 participants. These included 58 pediatric patients, 51 pregnant women, 214 adult females, and 224 adult males. Statistical analysis was performed using Python (Python Software Foundation, Wilmington, Delaware, United States). A p-value of < 0.05 was taken to be significant.  Result  The mean difference observed between NiADA and laboratory-estimated hemoglobin values came out to be -0.29 g/dL and -0.89 g/dL for adult females and males respectively, and 0.61 g/dL for pregnant women and -0.69g/dL for the pediatric population. The limits of agreement for NiADA were narrow at 2.77 to -2.18 g/dL for adult females, 3.76 to -1.96 g/dL for adult males, 1.89 to -3.29 g/dL for pregnant women, and 3.28 to -2.08 g/dL for the pediatric population. The sensitivity and specificity of the NiADA application against the laboratory estimation method were 75.8% and 53.8% for adult females, 70.0% and 48.3% for adult males, 23.8% and 90% for pregnant females, and 75% and 57% for the pediatric population.  Conclusion  As a non-invasive application, NiADA's performance is satisfactory and comparable with minimally invasive tools like HemoCue Hb 301 and other POCT devices.

摘要

背景

贫血是印度一个严重的公共卫生问题,影响着超过一半的人口。为减轻其对民众的负担,印度政府在“无贫血印度”计划下,采用了一种贫血诊断和治疗的监测策略。即时检验(POCT)设备在社区层面检测血红蛋白方面发挥着关键作用,因为社区没有复杂的实验室仪器。目前大多数可用的POCT设备本质上是侵入性的,有其自身的局限性。一种非侵入性的血红蛋白估计方法将解决侵入性POCT仪器的许多局限性,这将进一步提高人们对血红蛋白检测的接受度。非侵入性贫血检测应用程序(NiADA)(印度西孟加拉邦加尔各答的Monere AI私人有限公司,一种非侵入性POCT应用程序)使用人工智能(AI)从下眼睑图像预测血红蛋白水平。这种实时、即时护理、低成本的解决方案使用定制的计算机视觉深度学习算法来确定血液血红蛋白值。

方法

本研究将基于人工智能的智能手机应用程序NiADA与实验室血红蛋白估计以及一种广泛使用的即时护理血红蛋白估计仪器(HemoCue Hb 301;瑞典斯科讷省安吉尔霍尔姆的HemoCue AB公司)进行验证。该研究在印度东部的一家三级护理医院进行,共招募了556名参与者。其中包括58名儿科患者、51名孕妇、214名成年女性和224名成年男性。使用Python(美国特拉华州威尔明顿的Python软件基金会)进行统计分析。p值<0.05被认为具有统计学意义。

结果

NiADA与实验室估计的血红蛋白值之间观察到的平均差异,成年女性为-0.29 g/dL,成年男性为-0.89 g/dL,孕妇为0.61 g/dL,儿科人群为-0.69 g/dL。NiADA的一致性界限较窄,成年女性为2.77至-2.18 g/dL,成年男性为3.76至-1.96 g/dL,孕妇为1.89至-3.29 g/dL,儿科人群为3.28至-2.08 g/dL。NiADA应用程序相对于实验室估计方法的敏感性和特异性,成年女性分别为75.8%和53.8%,成年男性为70.0%和48.3%,孕妇为23.8%和90%,儿科人群为75%和57%。

结论

作为一种非侵入性应用程序,NiADA的性能令人满意,与HemoCue Hb 301等微创工具和其他POCT设备相当。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b75b/11280006/dbed5defc586/cureus-0016-00000065442-i01.jpg

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