Decode Health 利用人工智能实现更好的患者治疗效果
公司规模
11-200
地区
- America
国家
- United States
产品
- DataRobot AI Cloud
- AutoML
- Automated Time series
技术栈
- Machine Learning
- Predictive Analytics
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Innovation Output
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 医疗保健和医院
适用功能
- 产品研发
- 质量保证
用例
- 预测性维护
- 远程病人监护
服务
- 数据科学服务
关于客户
Decode Health 是一家医疗保健 AI 公司，为从诊断公司到制药公司等各种组织提供外包创新团队。该公司帮助其合作伙伴快速且经济高效地利用其数据解锁新发现。目前的项目包括基因组数据创建、RNA 诊断和人口健康分析。Decode Health 的工作具有预测性、主动性，并且可扩展到不断发展的医疗保健生态系统。在过去十年中，领导 Decode 的团队构建了一个框架，利用各种工具（包括先进的机器学习方法）来提供准确的结果。
挑战
医疗保健 AI 公司 Decode Health 一直依靠预测分析来利用数据发现新事物。然而，在早期，建模是一项缓慢的手动任务。分析一个数据集可能需要两到三周的时间，需要两到三名数据团队成员全天候工作。这种繁琐的手动工作包括大量时间准备数据、等待模型、重新校准和再次等待。该公司需要一种可以简化此流程并更快、更经济高效地提供准确结果的解决方案。
解决方案
Decode Health 转向 DataRobot AI Cloud 进行自动化机器学习，以帮助预测健康结果并推动更积极主动、更低成本的护理。DataRobot AI Cloud 简化了端到端的预测分析，使团队能够更有策略地专注于数据元素和理解结果。借助 DataRobot AI Cloud，该公司通过自动化机器学习增强了其框架，从而简化了端到端的预测分析。过去，对单个数据集的全面分析可能需要数周时间，需要多名数据团队成员全天候工作；现在，他们在几天内就能完成同样的任务。
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.
