根据参加赛事的命题要求可以看到当今机器学习给各行各业带来的应用泛化能力： 重点方向 一、医疗重点方向 / AI+Health Focus Areas 1）辅助诊断：利用NLP、知识图谱等核心技术实现病历、医疗文献的智能结构化、知识提取，从而辅助医生诊断、实现自动问诊机器人等应用场景。
1）Auxiliary diagnosis: the intelligent structure and knowledge extraction of medical records and medical documents can be realized by using core technologies such as NLP and knowledge graph, so as to assist doctors’ diagnosis and realize automatic consultation robot and other application scenarios.
2）医学影像：病灶识别标注、靶区自动勾画、影像三位重建等赋能医生快速读片、辅助勾画、提升放疗手术精度的人工智能产品、服务和通用能力。
2）Medical imaging: focus recognition marking, automatic target delineation, image reconstruction and other enabling doctors to quickly read films, assist sketching, improve the accuracy of radiotherapy surgery of artificial intelligence products, services and general capabilities.
3）新药研发：应用于靶点筛选、药物挖掘、药物优化、患者招募、服药依从性管理、患者数据收集等新药研发各环节的人工智能产品和通用能力研发。
3）New drug development: research and development of artificial intelligence products and general capabilities applied to target screening, drug mining, drug optimization, patient recruitment, drug compliance management, patient data collection and other aspects of new drug research and development.
4）健康管理：通过智能传感和人工智能技术相结合，实现对慢病管理、精神类疾病看护照料、母婴管理以及大规模人口健康管理的革新化服务。
Health management: innovative services for chronic disease management, mental illness care, maternal and infant management and large-scale population health management are realized through the combination of intelligent sensing and artificial intelligence technology.二、金融重点方向 / AI+Finance Focus Areas 1）智能保险：针对保险售前智能保顾、风险评估，售后智能核赔、风险控制等需求，研发人工智能产品和技术，赋能保险业发展。
1）Intelligent insurance: aiming at insurance pre-sale intelligent protection, risk assessment, after-sale intelligent verification, risk control and other needs, research and development of artificial intelligence products and technologies, to enable the development of the insurance industry.
2）信贷融资：利用人工智能技术提升银行对企业信贷融资信用评估、风险控制、流程管理的效率，缓解中小微企业融资信贷困难的挑战。
2）Credit financing: using artificial intelligence technology to improve the efficiency of bank credit evaluation, risk control and process management, and to alleviate the challenge of small and medium-sized micro-enterprise financing credit difficulties.
3）金融监管：利用自然语言处理、知识图谱等关键技术，提升对海量金融财年报等信息的结构化知识抽取效率，实现智能化事实核验、风险预警等功能，辅助金融市场监管。
3）Financial supervision: using key technologies such as natural language processing, knowledge graph and other key technologies to improve the efficiency of extracting structured knowledge from massive financial year reports, to achieve intelligent fact checking, risk early warning and other functions, and to assist financial market supervision.
4）智慧银行：结合“开放银行”趋势，研发人工智能产品服务，赋能银行实现线上线下、网点内外的客户智能服务和财富管理。
4） Smart bank: combine the trend of “open bank”, develop artificial intelligence product service, enable bank to realize customer intelligent service and wealth management both online and offline, inside and outside the network.
三、交通重点方向 / AI+Mobility Focus Areas 1）智能汽车: 为汽车加载视觉、语音等人工智能能力，提升汽车智能化，改善人车交互体验，辅助驾驶员安全、高效驾驶。
1）Intelligent vehicle: load vision, voice and other artificial intelligence capabilities for the car, improve automotive intelligence, improve human-vehicle interaction experience, and assist drivers to drive safely and efficiently.
2）交通治理：通过机器学习、智能传感的赋能，研发提升交通拥堵、事故异常等事件识别、预判、疏导能力的人工智能解决方案，全方位支撑人机协同的交通治理。
2）Traffic governance: through machine learning, intelligent sensing, research and development of traffic congestion, accident anomalies, such as event identification, prediction, channeling ability of artificial intelligence solutions, all-round support of man-machine coordination of traffic governance.
3）出行服务：通过人工智能技术与应用赋能，为实现不同出行、运输、服务目的的企业、个人提供高效、便捷、智慧、乃至无人自动的终端解决方案。
3）Mobility services: through artificial intelligence technology and application empowerment, to achieve different travel, transportation, service purposes for enterprises and individuals to provide efficient, convenient, intelligent, and even unmanned Mobility solutions.
4）车路协同：研发物联网传感设备、人工智能通用技术等，实现车车、车路协同感知与实时信息交互，支撑预判、决策，保证交通安全，提高通行效率。
4）Vehicle-road coordination: research and development of Internet of things sensing equipment, artificial intelligence technology, etc., to achieve vehicle, vehicle and road coordination perception and real-time information interaction, support prediction, decision-making, ensure traffic safety, improve traffic efficiency.
四、工业重点方向 / AI+Industry Focus Area 1）质量管控：通过机器视觉、机器学习等技术与机器人产品等，提升对生产质量的动态监测与把控，降低残品率，提升工作效率，改善生产工艺与流程。
1） Quality control:Through machine vision, machine learning and other technologies and robot products, improve the dynamic monitoring and control of production quality, reduce the rate of debris, improve work efficiency, improve production processes and processes.
2）生产设计：引入人工智能技术与机器人产品，实现个性化生产设计，提高生产柔性，满足市场不同客户需求。
2）Manufacturing and design: Artificial intelligence technology and robot products are introduced to achieve personalized production design, improve production flexibility, and meet the needs of different customers in the market.
3）物流供应：利用人工智能技术、机器人产品等方式有效动态实时监测库存需要，提升物流运输效率，降低库存成本风险。
3）Logistics supply: Using artificial intelligence technology, robot products and other ways to effectively and dynamically monitor inventory needs in real-time, improve the efficiency of logistics transportation, reduce the risk of inventory costs.
4）运维管理：通过历史数据挖掘学习、实时动态监测等方式，提升对工业制造设备的故障预测，精准安排日常运维，降低设备损耗和故障损失。
4）Operation and maintenance management: Through historical data mining learning, real-time dynamic monitoring and other ways, improve the industrial manufacturing equipment fault prediction, accurate arrangement of daily operations and maintenance, reduce equipment loss and failure loss.
