NeurAssist- An innovative AI-based neuro-imaging platform that assists clinicians with unbiased AI predictions and analytical tools.

2021年，超过五分之一的欧盟人口年龄在65岁及以上，预计到2100年，80岁及以上人口的比例将增加一倍以上（欧盟统计局）。这自然会增加与年龄有关的神经系统疾病的患病率，如痴呆和阿尔茨海默病。例如，世界上每三秒钟就有一人患上痴呆症。到2020年，全世界有5500多万人患有痴呆症。这一数字几乎每20年翻一番，到2030年达到7800万，到2050年达到1.39亿（世卫组织）。根据约翰霍普金斯大学医学院发表在《诊断》杂志上的一项研究，数据证实，不准确的诊断是导致严重医疗事故的头号原因。误诊的风险导致患者的医疗费用过高。例如，与正确诊断的患者相比，先前被误诊的血管性痴呆患者平均每年住院天数多40%- 143%，急诊室就诊次数多45%- 79%，门诊/医生就诊次数多19%- 48%，熟练护理机构就诊次数多61%- 221%，家庭保健天数多13%- 56%，每年对耐用医疗设备的索赔多44%。（2015, Craig A. Hunter, et）机器学习的兴起开启了分析结构神经成像数据的新方法，包括大脑年龄预测。（Elsevier B.V.）然而，我们发现了改进现有技术的机会。NeurAssist项目是一项基于人工智能的创新，可帮助神经病学临床医生进行预测诊断和视觉分析，以识别病理脑生物标志物，预测疾病，并使用最先进的机器学习方法支持数据解释。NeurAssist将加强对患者神经系统状况解释的准确性，提高医生和医疗专业人员预测的准确性，使其更容易做出正确的诊断。此外，它通过可解释的人工智能可视化算法提高了透明度、不偏不倚和可解释性，这有助于医生理解患者为什么会有特定的疾病。它可以通过降低误诊率来降低医疗成本，并为患者提供更快的结果——更好的诊断结果，对神经系统疾病的早期诊断。

In 2021, more than one fifth of the EU population was aged 65 and over, and the proportion of people aged 80 or over is projected to be more than double by the year 2100 (Eurostat). This naturally increases the prevalence of age-related neurological disorders such as dementia and Alzheimer's disease. For instance, someone in the world develops dementia every 3 seconds. There are over 55 million people worldwide living with dementia in 2020\. This number will almost double every 20 years, reaching 78 million in 2030 and 139 million in 2050 (WHO).According to a study conducted by the Johns Hopkins University School of Medicine and appearing in Diagnosis, data confirm that an inaccurate diagnosis is the No. 1 cause of serious medical errors. The risk of misdiagnosis lead to excessive medical costs for the patients. For example, Vascular dementia patients who were previously misdiagnosed had, on average, 40%--143% more inpatient days, 45%--79% more ER visits, 19%--48% more outpatient/physician visits, 61%--221% more skilled nursing facility visits, 13%--56% more home health care days, and up to 44% more claims for durable medical equipment per year, compared with patients correctly diagnosed. (2015, Craig A. Hunter, et)The rise of machine learning has unlocked new ways of analysing structural neuroimaging data, including brain age prediction. (2021 Elsevier B.V.) However, we identified opportunities to improve the current technologies. The project NeurAssist is an AI-based innovation that aids neurology clinicians with predictive diagnostics and visual analytics for the identification of pathological brain biomarkers, prediction of disease and support data interpretation using state-of-the-art approaches in machine learning.NeurAssist will strengthens the accuracy of interpretation of patient's neurological conditions, and it improves the predictive accuracy for the doctors and medical professionals to make correct diagnosis more often. In addition, it enhances transparency, unbiased and interpretability via explainable AI algorithms for visualisation, which helps the doctor to understand why the patient has a particular condition. It can reduce medical costs by reducing the rate of misdiagnoses and getting the faster results to the patients- the improved diagnosis results, early diagnosis to neurological conditions.