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朝聚眼科发布“AI眼科”医生 公司去年增收不增利,董事长张波洲:AI核心是提高医生的诊断效率

Core Viewpoint - The launch of the AI-assisted digital diagnostic tool "Zhang Mulan Doctor" by Cha Ju Eye Care aims to enhance diagnostic efficiency and patient experience in ophthalmology, amidst challenges in profitability and competition in the industry [2][4]. Company Overview - Cha Ju Eye Care, founded in 1988 and listed on the Hong Kong Stock Exchange in 2021, has a current market value of less than HKD 1.9 billion. It ranks first among private eye hospitals in Inner Mongolia, second in North China, and fifth nationwide based on total revenue in 2020 [3]. - In 2023, the company achieved a record net profit of CNY 229 million, but faced a nearly 15% decline in net profit year-on-year in the previous year, with gross margin dropping from 45.4% to 43.5% due to intensified competition and pricing pressures from national procurement policies [3]. Financial Performance - The company reported an increase in sales and distribution expenses by 18.7% year-on-year, reaching CNY 125 million in 2024, primarily due to marketing costs associated with newly acquired hospitals and existing facilities [3]. AI Implementation - The "Zhang Mulan Doctor" tool is designed to assist in clinical diagnosis by providing valuable insights that may be overlooked by doctors, thereby improving diagnostic accuracy and efficiency [4][7]. - The focus of the AI application is on collecting and synthesizing various types of information to support clinical decision-making, differing from other companies that may concentrate solely on AI imaging diagnostics [7]. Industry Context - The integration of AI in ophthalmology is not new, with several companies exploring AI applications in their operations. However, the profitability model for "AI + ophthalmology" remains unresolved [5][6]. - Companies like Eagle Eye Technology, which was an early entrant in the AI ophthalmology space, have faced significant challenges, including a dramatic decline in market value and ongoing losses, highlighting the difficulties in commercializing AI solutions in healthcare [6][7].