医生们创建的

由医生创建和监督,我们的医疗AI聊天机器人提供可靠和经过验证的支持。因为信任是我们的首要任务,Mediktor的准确性基于严格的医疗质量流程,这些流程验证我们的内容。我们医疗团队的任务是专业监督我们的评估者,并持续改进我们的标准。

Corp Scientific Intro

医生主导的数据库

大量医疗信息正在持续监控和更新。
这是我们数据的数字摘要。

+ 45K
疾病和症状的同义词
+ 9K
医学问题
+ 940
疾病
+ 3500
症状和疾病的插图

已验证医疗内容

的数据库经过严格的内部和外部验证过程。
这就是我们的做法。

内部验证

我们的医务部门执行严格的内部评估程序,以检验我们解决方案的准确性。

手动测试
我们的医务部门执行严格的内部评估程序,以检验我们解决方案的准确性。
自动测试
我们开发了一套动态的自动化测试,用于验证问题流与潜在疾病之间的正确关联。这些测试旨在适应可能的场景,从而使我们能够不断完善我们的算法并提高评估的准确性。
漫画格
我们的内容是使用称为漫画的样本案例进行验证的,这些漫画模拟了各种各样的迹象和症状。我们监控我们的NLP技术的性能,并确保在评估期间Mediktor的持续有效性。

外部专家审查

我们的数据库由专业人员开发,并由专家审核。专家分析我们的内容,提供个性化和全面的支持。

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热带病

Mediktor的数据库已经升级,可以准确检测热带地区最常见的疾病。

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感觉、身体和智力残疾

我们已经更新和审核了我们的数据库,以个性化残障人士的援助。

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心理健康

我们提供可靠的心理健康援助,已经得到专家的彻底分析。

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妇产科

所有妇产科信息和内容均经过严格的审查和批准流程。

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LGBTQIA+

我们根据相关信息,如性别或过渡治疗,调整了我们的医学评估。

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科学试验

Mediktor与相关外部组织合作,进行与真实患者的临床试验。

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Mediktor®体验:一种基于人工智能的新型症状评估器,适用于急诊服务中的患者

对 Mediktor 在低复杂度病症诊断方面与医生的准确性进行评估。评估该解决方案在医院急诊中的表现。

巴塞罗那诊所医院

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对医院急诊部门患者分类诊断决策支持系统的评估

曼彻斯特分诊、急诊科最终诊断以及Mediktor分诊和预诊断的比较。它测试了技术辅助分诊过程的潜力。

圣卡洛斯临床医院

马德里,西班牙。2018年

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在哥伦比亚波哥大圣依纳爵大学医院急诊部接受治疗的患者中使用Mediktor®(人工智能)的经验。

评估 Mediktor 与急诊医生在诊断和实验室检测方面的一致性的研究。证明 Mediktor 是一种可靠的工具,可帮助诊断急诊情况下最常见的疾病。

圣伊格纳修大学医院

波哥大,哥伦比亚。2019年

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基于人工智能算法的神经系统分诊工具在普通人群中的验证

评估 Mediktor 在神经科学服务中早期检测中风症状的有效性的论文。证明了软件在神经系统专业三级分类中的有效性。

巴尔德埃布隆医院

巴塞罗那,西班牙。2021年。进行中。

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基于人工智能算法的妇产科急诊先进分诊工具评估

该研究旨在比较 Mediktor+ 在妇产科专科分诊中与 MAT 分诊相比的效果。详细说明了该工具如何根据患者的紧急程度引导患者。

圣十字圣保罗医院

巴塞罗那,西班牙。2022年。进行中。

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将护理咨询与人工智能软件集成到 Parc Taulí 急诊服务的需求管理中。

在公立医院,护士们在Mediktor+的支持下评估了低复杂性病症的论文。展示了这种解决方案如何支持急诊需求管理,同时赋予了护理部门更多权力。

塔乌利公园大学医院

萨瓦德尔,西班牙。2022年。进行中。

相关文章

29/05/2024
HUAV Partners with Mediktor for Improved Urgent Care Management

Hospital Universitario Arnau de Vilanova (HUAV) is a healthcare provider in Lleida, Alto Pirineo y Arán, and parts of La Franja in Aragón, Spain. Healthcare professionals were struggling with overcrowded waiting rooms, and the HUAV was looking for a digital solution to help manage urgent care effectively. 

Serving approximately 400,000 people, the hospital’s Emergency Department often experiences overcrowding, particularly during high-demand seasons like autumn and winter. “In winter, we have a really hard time because we triple or quadruple the real capacity,” explained Nuria Amador, Nurse of the HUAV’s Emergency Department.

In recent years, the HUAV has undergone a significant demand increase at the ED, with nearly 50% of emergency visits being non-urgent (IV and V triage levels). This rise in non-urgent visits is often caused by a lack of public awareness about alternative public healthcare services more suitable for patients with low-complexity needs, resulting in unnecessary congestion in the central hospital emergency department.

In response to this challenge, the HUAV sought a digital solution to manage urgent care cases more effectively. The answer was a reverse referral model designed to identify non-urgent patients in the emergency waiting room and redirect them to Lleida’s Urgent Primary Care Center (CUAP). “What we were looking for by adding artificial intelligence with Mediktor was to give an extra point of quality to the reverse referral process,” said Oriol Yuguero, Head of the Emergency Department. 

Mediktor’s AI-driven software helped streamline the reverse referral model by meeting the hospital’s strict security standards and seamlessly integrating into its existing processes. Patients identified as having lower urgency levels (IV and V) through a traditional nurse triage were given the option to assess their symptoms using Mediktor’s software. This second AI-based assessment helped identify patients who could be seen at the CUAP and received a recommendation to leave the ED.

The results of this innovative approach were enlightening. Among those patients that Mediktor recommended to attend the CUAP, an impressive 90.9% left the Emergency Department. When patients receive and acknowledge Mediktor’s recommendation, they realize that their cases can be solved outside urgent care. This not only reduces their wait times but also empowers them to take control of their healthcare decisions. Most of these patients proceeded to the CUAP, where they received timely care and were subsequently discharged.

The implementation of Mediktor’s AI-driven reverse referral process has yielded significant benefits. For patients, it meant receiving appropriate care more quickly and efficiently. Those with non-urgent conditions were successfully redirected to CUAP, reducing their wait times and ensuring they received the care they needed without unnecessary delays. 

The AI-powered reverse referral process not only benefited the patients but also had a positive impact on healthcare professionals. It helped alleviate the burden on HUAV’s emergency department, allowing for better management of time and resources. Nurses, in particular, played a crucial role in this process, actively engaging in patient evaluation and discharge. The model also contributed to better patient education, helping individuals understand the healthcare system and navigate it more effectively. “The aim is that services can be optimised and used in a correct way and, at the same time, provide health education”, expressed Sílvia Solís i Vidal, Director at CUAP Prat de la Riba of Lleida.

The successful collaboration between HUAV and Mediktor stands as a testament to the transformative power of technology in healthcare delivery. By leveraging AI to manage urgent care demand, HUAV has not only improved patient outcomes but also enhanced operational efficiency. This success story underscores the hospital’s dedication to innovation and excellence, setting a new standard for healthcare in the region and beyond. 

29/03/2024
Hospital Clínic Barcelona Collaborates with Mediktor for Improved Patient Assistance in Tropical Diseases
14/02/2024
Mediktor’s AI Integration at Parc Taulí Sets a Milestone in Spain’s Public Health History
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Mediktor 是一种一类医疗器械

我们基于人工智能的医疗聊天机器人在症状初现时为患者提供了出色的服务,因此获得了一类医疗器械认证。
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