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Automating Directly Observed Therapy as a Platform Technology

Automating Directly Observed Therapy as a Platform Technology
将直接观察治疗自动化作为平台技术
批准号:
8670794
负责人:
Adam Hanina
金额:
$88.83万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-06-04 至 2016-04-30

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Introduction: Ai Cure Technologies LLC was established in 2009 to develop automated medication adherence monitoring solutions using computer vision technology. This SBIR Phase II will allow Ai Cure Technologies to test the accuracy and validity of its flagship product, AiView". The SBIR Phase I demonstrated that the AiView" platform was technically feasible and capable of confirming medication administration. Significance: Poor medication adherence is a huge burden on clinical research and clinical practice. The inability to accurately measure or improve adherence significantly compounds the problem. Clinical trials depend on people taking the drug being tested. The problem of medication adherence has been addressed - determinants of adherence are being studied and new monitoring methods developed - but no solution has been able to accurately confirm real-time medication adherence while also being affordable, flexible, and likable. The Product: Ai Cure Technologies will provide an automated DOT (Directly Observed Therapy) software platform, AiView", for use in clinical trials which uses sophisticated computer vision technology on webcam- enabled smart phones or tablets to visually confirm medication administration. AiView" will visually track and confirm medication administration without human supervision. Long-Term Goal: The AiView" system will combine sophisticated computer vision technology with the best attributes of DOT for 1/400th of the cost. Automating and standardizing the way medication adherence is captured will help clinical trials better define their subjects' rates of compliance and allow them to intervene immediately in case of non-compliance. Phase II hypothesis: AiView" can be used to accurately measure and improve medication adherence across different patient populations, and positively impact self-perception and clinical outcomes. Specific Aim #1: To demonstrate that the AiView" system can accurately measure and improve medication adherence in a depression and a stroke patient population. Specific Aim #2: To demonstrate that the AiView" system can improve self-perception and improve clinical outcomes in the AiView" intervention groups Expected Outcome: The patients in the AiView" intervention groups (depression and stroke) are expected to have statistically significant higher adherence rates than those in the pill counting groups.
期刊论文(1)
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会议论文
DOI: 10.1161/strokeaha.116.016281
发表时间: 2017-05
期刊: Stroke
影响因子: 8.3
作者: [Labovitz DL, Shafner L, Reyes Gil M, Virmani D, Hanina A]
通讯作者: Hanina A
A Digital Therapeutic for Pain Relief through AI-Guided Visual Stimulation
  • 批准号:
    10561374
  • 项目类别:
  • 资助金额:
    $5.5万
  • 财政年份:
    2021
  • 负责人:
    Adam Hanina
  • 依托单位:
A Digital Therapeutic for Pain Relief through AI-Guided Visual Stimulation
  • 批准号:
    10325724
  • 项目类别:
  • 资助金额:
    $31.95万
  • 财政年份:
    2021
  • 负责人:
    Adam Hanina
  • 依托单位:
Automating Directly Observed Therapy as a Platform Technology
  • 批准号:
    8524716
  • 项目类别:
  • 资助金额:
    $89.58万
  • 财政年份:
    2013
  • 负责人:
    Adam Hanina
  • 依托单位:
Funding of Phase II SBIR Contract. N44 DA-12-2227
  • 批准号:
    8756304
  • 项目类别:
  • 资助金额:
    $99.75万
  • 财政年份:
    2013
  • 负责人:
    Adam Hanina
  • 依托单位:
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