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The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

This study aims to explore the potential benefits favoring the adaptation of structural optimization techniques in the additive manufacturing (AM) of medical utilities to meet the repetitive demand for functionally precise customized orthoses. Irregularities encountered during the conventional treatment of tendon injuries can be eschewed using advanced structural simulation in design and innovative splint fabrication using 3D printing.

A customized mallet finger splint designed from 3D scans was subjected to ANSYS topological simulation comprising multi-level weight reduction to retain optimal mass (100%, 90%, 80%, 70% and 60%). A batch of the four typical 3D printing materials was chosen to conduct a comparative mechanical and thermal stress analysis, facilitating the selection of the optimal one for fabricating functionally adaptive splints. Assurance of structural safety was accomplished through the experimental validation of simulation results against the testing data set of ASTM D695 and ASTM D638 Type-1 specimens over a universal testing machine (UTM). Fused deposition modeling (FDM) 3D printing processed the optimized splint fabrication to assist evaluation of weight reduction percentage, fitting aesthetics, appearance, comfort, practicality and ventilation ease at the user end.

AM efficacy can efficiently execute the design complexity involved in the topology optimization (TO) results and introduces rehabilitation practicality into the application. Topologically optimized splint provided with favorable comfort, stiffness and strengthening features, offers ventilation ease and structural stability for customized appliances, with 30.52% lighter weight and 121.37% faster heat dissipation than unoptimized one.

The state of art multidisciplinary optimization featured with structural and material optimization attributes can deliberately meet medical necessity for performance-oriented orthotic devices.