Smart Occupational Health Service

智能职业健康服务应用程序旨在提高中小企业，微型组织以及自雇人士对这些服务的接受程度。我们项目的一个关键创新方面是使用先进的人工智能算法和模型来进行评估，并将用户与专业职业健康服务提供商进行匹配。这将确保更个性化的方法，并增加用户获得满足其要求的服务和特定干预措施的可能性。雇主及其员工将是我们方法的重点。自我评估将要求他们提供对需求的感知，然后应用程序将这些与适当的干预相匹配。雇主将收到匿名调查数据和建议，以确保相关的职业健康服务，从我们全面的英国范围内的目录。例如，心理健康谈话疗法，新的初学者健康筛查，角色特定的医疗，肌肉骨骼，人体工程学，虚拟诊所，合理的调整建议，等等。评估可以在一段时间内进行，以跟踪和响应新出现的需求。我们将采用渐进式开发方法，我们将：1.在探索更高级的模型之前，先开发简单、快速的模型进行基准测试和测试。2.与职业健康专家协商制定评分标准。使用平台的评估数据完善机器学习推荐系统。4.使用机器监督学习方法，我们将训练，验证和测试由职业健康专家标记的数据集。5.应用先进的人工智能技术，包括“ChatGPT”来理解用户数据，并根据用户的相似性将其聚类在一起，以帮助识别正确的职业健康服务。6.确保持续的用户保留系统，人工智能将使用对评估问题的响应来跟踪用户数据，以优化推荐的解决方案。7.我们的平台将通过提供个性化的职业健康服务方法、增加可访问性和利用现有数据来不断改进我们的模型，以应对挑战的不同方面。这种集成的解决方案确保用户获得最佳的职业健康服务体验，并确保我们的模型随着时间的推移不断改进。

The Smart Occupational Health Services app aims to improve the uptake of these services among SME, micro-organisations as well as the self-employed.A key innovative aspect of our project is the use of advanced artificial intelligent algorithms and models to score assessments and match users to specialist occupational health service providers. This will ensure a more personalised approach and increase the likelihood of users accessing services and specific interventions that meets their requirements.Employers and their individual employees will be the focus of our approach. A self-assessment will ask them to provide perception of needs and then the app will match these to an appropriate intervention. Employers will receive anonymised survey data and recommendations for securing relevant occupational health services from our comprehensive UK wide directory. For example for mental health talking therapies, new starter health screening, role specific medicals, musculoskeletal, ergonomics, virtual clinics, reasonable adjustment recommendations, and more. Assessments can be conducted overtime to track and respond to emerging needs.We will adopt an incremental development approach where we will:1. Develop simple, quick models for benchmarking and testing before exploring more advanced models.2. Develop scoring criteria in consultation with occupational health experts.3. Refine machine learning recommender systems using the platform's assessment data.4. Use machine supervised learning approaches where we will train, validate and test datasets labelled by an occupational health specialist.5. Apply advanced artificial intelligent techniques including 'ChatGPT's' to understand user data and cluster users together based on their similarities to help identify the right occupational health services.6. Ensure ongoing user retention systems where artificial intelligence will use responses to assessment questions tracking user data over time to optimise recommended solutions.7. Widely consult employers and individuals to develop a compelling and friendly user interface.Our platform will tackle different aspects of the challenge by providing a personalised approach to occupational health services, increasing accessibility and leveraging existing data to continuously improve our models. This integrated solution ensures that users receive the best possible occupational health service experience and that our models continue to improve over time.