Smart Occupational Health Service

智能职业健康服务应用程序旨在促进中小企业、微型组织和自雇人士对这些服务的接受。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为评估评分，并将用户与专业职业健康服务提供商配对。这将确保更个性化的方法，并增加用户获得满足其需求的服务和特定干预的可能性。雇主及其个别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需求与适当的干预相匹配。雇主将从我们全面的英国范围目录中收到匿名调查数据和确保相关职业健康服务的建议。例如，心理健康谈话疗法、新的初学者健康筛查、特定角色的医疗、肌肉骨骼学、人体工程学、虚拟诊所、合理的调整建议等等。评估可以超时进行，以跟踪和响应新出现的需求。我们将采用增量开发方法：1.在探索更高级的模型之前，为基准和测试开发简单、快速的模型。咨询职业健康专家制定评分标准。使用平台的评估数据改进机器学习推荐系统。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。应用先进的人工智能技术，包括“ChatGPT‘s”，以了解用户数据，并根据用户的相似性将用户聚在一起，以帮助识别合适的职业健康服务。确保持续的用户保留系统，其中人工智能将使用对评估问题的响应来跟踪随时间推移的用户数据，以优化建议的解决方案。7.我们的平台将通过为职业健康服务提供个性化的方法、增加可访问性和利用现有数据来不断改进我们的模型，从而应对挑战的不同方面。这一集成解决方案确保用户获得尽可能最佳的职业健康服务体验，并确保我们的模式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.