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【2021 Application Example】 Life-saving is as urgent as a spark AI critical illness system monitors and grasps the golden rescue period

60-year-old Mr. Huang was admitted to the hospital due to a stroke. After lying in the intensive care unit for two weeks, his condition suddenly took a turn for the worse. After rescue, he was lucky enough to survive. In fact, with the assistance of AI critical illness early warning technology, hospitals can detect signs and take timely and accurate medical measures 6-8 hours before a patient's heart stops, which can greatly reduce the chance of death in the hospital.

The deterioration of the condition is a process that evolves over time, and its subtle changes are by no means without context. Previous research reports show that about 60 to 70% of inpatients who experience unexpected in-hospital cardiac arrest had symptoms 6 to 8 hours before their cardiac arrest, but only a quarter of them were recognized by clinical staff. Detection and discovery, therefore, there is a need for a risk warning tool or system that can be used earlier and continuously to monitor the condition, alert medical staff to pay attention to subtle changes in the patient's condition at any time, and take timely and accurate intervention measures before the condition progresses to effectively reduce adverse events. or the risk of serious adverse events.

Unexpected deterioration cannot be detected early

Acute and severe patients often undergo unpredictable changes, and timely detection or prediction of potential acute and severe patients is an important issue. The currently commonly used clinical assessment method is Modified Early Warning Score (MEWS), which uses simple physiological parameter assessment (including heartbeat, respiratory rate, systolic blood pressure, body temperature, urine output and state of consciousness) to screen out high-risk patients, and has been proven to be predictive. Patient clinical prognosis.

MEWS is a scoring mechanism with a single time point and a standardized formula. However, the AI ​​​​crisis warning system developed by Boxin Medical Electronics - Hospital Emergency and Critical Care Early Warning Index System (EWS) is designed to predict patient status with immediate response. , collect the physiological data of patients over time for deep learning, find the best prediction model, and improve the overall accuracy.

Boxin Medical Electronics uses a big data analysis model to build an early warning system (EWS), IoT Internet of Things and 5G communication technology, allowing medical staff to remotely monitor the physiological status of patients through communication equipment, and monitor emergency and severe cases quickly The patient's condition changes and the golden rescue period of 6-8 hours before cardiac arrest can be grasped.

Boxin Medical Electronics imports AI vision After interpretation, unmanned operation can greatly reduce medical care manpower

▲After Boxin Medical Electronics introduces AI visual interpretation, unmanned operation can greatly reduce medical manpower

The AI ​​technology developed by Boxin Medical Electronics is the Gradient Boosting Ensemble Learning System (GBELS) to build an early warning system. It is a learning-based EWS prediction algorithm developed by the company, which is an integrated learning ( Ensemble Learning) and is classified as supervised learning, providing the following three functions:

1. Early warning risk notification is used to analyze representative data using GBELS to provide an early risk score so that medical staff can conduct immediate clinical assessment and provide appropriate medical treatment.

2. Reduce medical manpower: Collect continuous physiological monitoring data, such as heartbeat, respiration, blood pressure and blood oxygen concentration, etc., to reduce the time for medical staff to write cases.

3. Combine IOT logistics network and 5G communication technology to quickly transmit medical data such as monitoring parameters and imaging data, and assist medical staff to monitor changes in patients' condition remotely through communication equipment.

AI critical illness system monitoring to master the golden treatment period

Boxin Medical Electronics stated that assessing the severity of the disease in acute and severe patients is a complex task, and patients often experience unpredictable changes. Clinical medical staff often judge the condition based on their own clinical experience or intuition, which lacks science and objectivity, resulting in the inability to correctly identify and timely detect potentially acute and severe patients, resulting in or misdiagnosis leading to increased in-hospital mortality of patients. The introduction of an AI early critical illness warning system can assist emergency and critical care medical staff to correctly predict the patient's condition and allow patients to receive the care they need immediately. This can reduce the manpower arrangement of the emergency and critical care ward at the same time and reduce labor costs.

In addition, the easy-to-carry design will help the system be introduced into ambulances, home care and other places in the future, so that emergency patients can receive appropriate care earlier. Other departments within the hospital can also develop new applications around this system, which can effectively accelerate the development and promotion of smart medical technology. With the COVID-19 epidemic still raging in many countries around the world, this system can also help hospitals in various places to operate more effectively. Caring for and monitoring the condition of critically ill patients.

In addition to AI critical illness warning, Boxin Medical Electronics has also developed AI image interpretation - Medical Physiological Monitor Life Cycle Compliance Testing (AVS), which uses AI image interpretation technology to develop automated quality inspection of life support medical equipment. The instrument solves the time-consuming problem of medical instrument testing. It can reduce testing time by 70%, increase the number of tests by 3 times, and effectively reduce labor costs by 50%. At the same time, it is 100% compliant with regulatory requirements, and gradually solves the shortage of manpower and medical resources in the medical field. , medical work overload and other issues. It has now taken root in mainland China and is actively preparing for its launch in Europe. It will develop towards the Japanese and American markets in the future.

Boxin Medical Electronics develops AI image interpretation-medical Physiological monitor life cycle compliance testing (AVS) solves the problem of time-consuming testing of medical equipment and can reduce testing time by 70%

▲Boxin Medical Electronics develops AI image interpretation-medical physiological monitor life cycle compliance testing (AVS) to solve the time-consuming problem of medical instrument testing and can reduce testing by 70% time.

At this stage, Boxin Medical's smart medical technology has been introduced into medical hospitals including Hsinchu MacKay, Changkei, Dongyuan General Hospital, Kaohsiung University of Technology Affiliated Hospital, Zhenxin Hospital, Hsintai Hospital, Taipei Medical University Affiliated Hospital, etc. GE Healthcare.Inc, an internationally renowned medical materials manufacturer, and Mindray Medical, China's largest medical materials manufacturer, are both representative customers of Boxin Medical Electronics.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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【解決方案】佐翼科技無人機導入高爾夫球場域 可節省一半人力
Droxo Tech Applies Drones in Golf Courses to Reduce Manpower by Half

For most golf courses, the operations and management is a headache "Golf courses are selling turf and need to be properly taken care of," a golf course manager bluntly pointed out Facing the market pain points of labor shortage, aging population and high cost, the use of AI drones for pesticide spraying and pest control will reduce labor costs by more than half and greatly improve the overall operational efficiency At noon in early summer, an AI drone is slowly taking off at the Taipei Golf Club in Taoyuan Its main task is to test AI drone fertilizing and pesticide spraying on the golf course In fact, drones of Droxo Tech, the company performing this task, are widely used for fertilization, pesticide spraying, and pest and disease control for rice, bananas, and tea trees For golf courses with turfs that often cover tens to hundreds of hectares, AI drones are needed to assist in turf maintenance Data collection, development of pesticide spraying AI models, and multispectral image 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【解決方案】搭上綠能商機 華鉬實業打造全釩液流電池儲能系統設備 長效儲能的最佳選擇
Taking advantage of green energy business opportunities, Hua Molybdenum Industry creates all-vanadium redox flow battery energy storage system equipment, the best choice for long-term energy storage

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【解決方案】優式AI智能割草機器人 搶攻高爾夫藍海市場
USRROBOT's AI Lawn Mowing Robot Enters the Blue Ocean of Golf Market

An AI smart lawn mowing robot, resembling a vacuum robot, shuttles back and forth on the 30-hectare golf course lawn for weeding This robot, independently developed and designed by Taiwanese, is equipped with the world's first electronic fencing positioning technology which utilizes high-precision GPS integrated with cloud AI computation to determine the most efficient mowing paths, targeting the lucrative blue ocean market of golf courses This AI lawn mowing robot was developed by USRROBOT, a Taiwanese startup established in 2019 Chao-Cheng Chen, the president of USRROBOT, once served as the executive vice president of one of the top five ODM tech companies in Taiwan, and specializes in software and hardware integration When he served as the chairman of the Service Robot Alliance, he knew that the service robot industry was bound grow rapidly due to declining birth rates and the growingly severe labor shortage New demand - The horticulture market is large and the has rigid demand "To develop the core technology of service robots, we must find rigid demand Looking at European and American countries, there is a shortage of labor, but demand for horticulture has increased, and there has been a long-term shortage of 7-10 of horticultural workers" Under this strong "rigid demand," Chao-Cheng Chen established USRROBOT, and the company's first product is the AI lawn mowing robot In terms of overseas markets, the United States is the world's largest horticulture market, accounting for 30-40 of the global output value It is estimated that there are about 1 million horticulture workers, but they have been experiencing a labor shortage of 7-10 in recent years and have not been able to improve the situation The main reasons for labor shortage are Aging population and gardening is a labor-intensive job, so young people don't want to do it Unlike in Taiwan, European and American countries attach great importance to lawn maintenance and have expressly stipulated in the law that heavy fines will be imposed for failing to mow the lawn Therefore, the AI lawn mowing robot has considerable market development potential The introduction of AI multi-device collaborative mowing sensor technology is expected to reduce the burden of staff maintaining the golf course The AI lawn mowing robot developed by USRROBOT is currently in its second generation Domestic universities and well-known art museums are using the latest model M1, and it is also being used by some world-renowned high-tech companies and well-known universities in the United States The company is currently involved in negotiations for subsequent business cooperation USRROBOT stated that the professional RTK system currently used can reduce the original GPS positioning error from tens of meters to about 2 centimeters, allowing the robot to move accurately outdoors After setting the boundaries, it can be easily operated using the app New application - 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Expert systems are needed to overcome difficulties with different grass species "This AI lawn mowing robot has low noise, low pollution, low labor costs, and is waterproof and anti-theft In the lawn mowing process, it can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality, maintaining aesthetic and consistent grass length" Chao-Cheng Chen went on to say that the most important part about golf courses is that the grass pattern should be beautiful and free from diseases and pests Based on the site survey, golf courses are mainly divided into three major areas green, fairway and rough There is no problem using the current mowing robot to mow the rough area, and it can overcome slopes within 20 degreesThe short grass in the fairway area may only be two centimeters long, and the grass types are also different, so the cutterhead design needs to be modifiedAs for the grass in the green area, the grass must be mowed close to the ground and maintained in a consistent direction because it affects the putting speed Many factors will affect the green index, and this part requires more research and testing The AI lawn mowing robot can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality The AI smart lawn mowing robot has a built-in camera that can be used to detect the health condition of the lawn Chao-Cheng Chen said that in the future, an expert system will also be introduced for early determination of whether there are diseases, pests in the lawn or whether there is sufficient moisture, and provide lawn health data analysis to customers, so that they can take preventive and response measures sooner to reduce disaster losses Chao-Cheng Chen, who is also a good golfer himself, said that golf has developed well in Taiwan However, due to weather factors, such as rainy and humid climate and typhoons, Taiwan's golf courses have harder soil and more potholes compared with top tier golf courses overseas If AI lawn mowing robots are to be widely introduced into golf courses, there are still many difficulties that must be overcome However, Taiwan's difficult terrain creates a good testing ground Once Taiwan can overcome the many problems and successfully introduce the robot, it will be able to expand to overseas markets and seize new market opportunities in a blue ocean Chao-Cheng Chen, President of USRROBOT nbsp