Chang Gung Memorial Hospital, Linkou

Osteoporosis and the associated low-impact fracture is a global problem, particularly in the aging population. Patients with a femoral neck fractures had a higher mortality rate; for patients older than 65 years, 20% of them died within one year from fracture. The prevalence of osteoporosis among people older than 50 years is estimated at approximately 30%; however, only 10% of them are diagnosed. Furthermore, only 27% of the people who had fractures undergone bone density testing. These data suggest a large unmet medical need in the detection of osteoporosis. The gold standard modality to measure bone mineral density (BMD) is the dual-energy x-ray absorptiometry (DXA). However, cost and accessibility prevents its large scale population screening. In contrast, plain pelvis film is standard x-ray which is of low cost and has a much higher population coverage and accessibility. Therefore, we developed a deep learning algorithm that can detect bone density directly by conventional pelvic X-rays. We had obtained a large number of patients with the pelvic X-ray images and their DXA reports to train a deep learning algorithm to extract subtle image features that can be used to estimate the BMD. The model is accurate in detecting people with osteoporosis (T-score

Chang Gung Memorial Hospital, Taoyuan, Taiwan

Background
Maxillomandibular advancement(MMA) is the most effective surgical treatment for patients with obstructive sleep apnea(OSA). However, the perioperative management is crucial to keep patients safe from various critical complications. The aim of this study is to review the perioperative management of patients undergoing MMA.
Method
A retrospective review of medical records was conducted on OSA patients underwent MMA in Craniofacial Center, Chang Gung Memorial Hospital. The parameters monitored are clinical history, anaesthetic evaluation before surgery, intraoperative events, anaesthesia records, recovery room records and progression notes during admission. A comparison of plysomnographic indices before and 3 months after surgery is performed to exam the efficacy of MMA.
Results
Of consecutive 123 patients, aged 32(±9.8) and 80% were male. The BMI was 23.2(±3.2)kg/m2. The Apnea-Hypopnea Indices were 31.06(±23.7) and 4.5(±7.6)/hr before and after surgery. The American Society of Anaesthesiologist(ASA) score was II in 114 and III in 9 patients. During surgery, hypotensive anaesthesia with blood pressure of 50(±2.1)mmHg and HR 74(±7.9)/min were maintained. The average blood loss calculated during surgery was 929(±452)ml. All the patients were extubated in the operating room and kept in recovery room for observation before they were transferred in the ward. Patients stay in the hospital for 3(±1.4) nights before discarge. No patients required reintubation or emergent tracheostomy.
Conclusion
Following proper patient selection, meticulous anesthetic control, and precise surgical conduction, relief of intermaxillary fixation and endotracheal extubation can be a standard procedure. With comprehensive management, OSA patients undergoing MMA may experience a safe and non-critical perioperative care, and expeditious recovery.

Chang Gung Memorial Hospital,Linkou

The adoption of new technologies in the trauma field can improve the treatment and the outcome of the patients. Hip fractures are the leading type of fracture in elderly individuals and commonly see in the emergency department. Early diagnosis and management of hip fractures might preserve the joint\'s function, ambulation, and quality of life of the patient and reduced complications. The initial misdiagnosis of hip fractures will lead to advert consequences. However, the misdiagnosis of hip fracture remains in the chaos and busy emergency room with multiple patients or inexperienced physicians. In the emergency room, the physicians have to rapidly and precisely treat the trauma patients, where artificial intelligence can help.
The deep learning algorithm emerged in several medical image domains which proved to have promising performance. Our team developed a deep learning based computer-assisted hip fracture diagnosis system which can assist the primary physician to rapidly detect the possible fracture site. Once the diagnosis can be made earlier, the patient can receive definite treatment earlier. We also developed a human-AI collaboration mechanism to improve the diagnostic accuracy of physicians to make diagnoses precisely and improve the quality of medical care.

Changhua Christian Hosipital

Multiple risk factors may lead to pharmacist dispensing errors, such as medications with look-alike, sound alike characteristics, with multiple strengths, with multiple dosage forms or human factors including not familiar with the medication cabinets, fatigue, not exactly making double check.
Changhua Christian Hospital began to cooperate with academic research units in developing Cell Indicator System for Pharmacies since 2014. Through this system, pharmacists can use barcode scanner to scan QR code from the medication bag, and then LED lights up to indicate the correct type of drug to fill. Pharmacists can fetch the correct medications based on the intelligent designs of visual instruction (light, color), verbal instructions and gesture sensors. This system can also support with different dosage forms in cabinet shelves or drawers.
This Smart Cell Indicator System can satisfy the requirement for dispensing in Taiwan. We believe this system can prevent dispensing error effectively, reduce pharmacist workload, and improve dispensing efficiency. Therefore, pharmacists can spend more time on direct patient care and improve the pharmaceutical care quality.

Changhua Christian Hospital

Fall Prevention Center (FPC) in Changhua Christian Hospital (CCH) has been committed to establish the health care system that ensures patient safety for years. It aims to prevent patient falls and decrease fall-related injuries. Our transdisciplinary team has developed a “mobile smart infrared bed-exit monitor” (Monibed). This product uses multiple infrared modules to monitor the behavior of patients and to reduce the false alarm. The device features include two sit-up/bed-exit modes for monitoring and highly mobile design for easy installation. The Monibed is compatible with most nurse call system, and equipped with Wi-Fi for smart medical care use. It also solves privacy concerns, which is frequently questioned by using the surveillance camera. The monitor has been patented in Taiwan, US, and China. It could be applied in healthcare institutes and home to reduce accidental falls of the patients and the burden of caregivers

Changhua Christian Hospital

We develop a UV-box system which can detect very low density of fluorescence in hands, automatically take the image of hands, and calculate the percentage of un-cleaning area of hands.

Charsire Biotechnology Corp.

1. Sanovazo trauma dressing
2. CELLUTIMA Cosmeceutical products for post laser treatment

CHENG GUNG MEMORIAL HOSPITAL, Linkou

Target OB
A novel maternal fetal health care model with di gital and telemedicine features

Chi Lai Biotechnology Co., Ltd.

CONTIN was established to help resolve the founder's long-term scalp issues
which could not be accomplished using any product currently on the market.
The crucial element of CONTIN's patented plant extract shampoo is an
enzyme extracted from garlic that has been fermented for 120 days.

Chi Mei Medical Center

A communication system combining with visual and audio signal for deaf.
Rethinking the distribution of hepatitis C virus genotypes from a historical perspective
Importing all-round intelligent equipment- A new era of microbiological testing
Precision Radiation Therapy at Chi Mei Medical Center
LC/MS/MS testing and development- From mg/L to pg/L