[Digital transformation of a routine histopathology lab : Dos and don'ts!] / Digitalisierung der histopathologischen Routinediagnostik : Dos and Don'ts!

The implementation of digital histopathology in the laboratory marks a crucial milestone in the overall digital transformation of pathology. This shift offers a range of new possibilities, including access to extensive datasets for AI-assisted analyses, the flexibility of remote work and home office arrangements for specialists, and the expedited and simplified sharing of images and data for research, conferences, and tumor boards. However, the transition to a fully digital workflow involves significant technological and personnel-related efforts. It necessitates careful and adaptable change management to minimize disruptions, particularly in the personnel domain, and to prevent the loss of valuable potential from employees who may be resistant to change. This article consolidates our institute's experiences, highlighting technical and personnel-related challenges encountered during the transition to digital pathology. It also presents a comprehensive overview of potential difficulties at various interfaces when converting routine operations to a digital workflow.

Human Centered Decision-Making for COVID-19 Testing Center Location Selection: Tamil Nadu-A Case Study.

This paper proposes a blend of three techniques to select COVID-19 testing centers. The objective of the paper is to identify a suitable location to establish new COVID-19 testing centers. Establishment of the testing center in the needy locations will be beneficial to both public and government officials. Selection of the wrong location may lead to lose both health and wealth. In this paper, location selection is modelled as a decision-making problem. The paper uses fuzzy analytic hierarchy process (AHP) technique to generate the criteria weights, monkey search algorithm to optimize the weights, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the different locations. To illustrate the applicability of the proposed technique, a state named Tamil Nadu, located in India, is taken for a case study. The proposed structured algorithmic steps were applied for the input data obtained from the government of India website, and the results were analyzed and validated using the government of India website. The ranks assigned by the proposed technique to different locations are in aligning with the number of patients and death rate.

TEAM(ing): together each achiev(ing) more!

Providing medical care at the highest levels across various reproductive endocrinology and infertility settings necessitates seamless partnership among multiple people with diverse skill sets. In this introductory article for this month's Views and Reviews, the concept of teaming is presented, including the key concepts of collaboration, assembling the right team members, establishing goals, inspiring and empowering others, and encouraging new approaches to optimize outcomes. Following this introduction, thought leaders from diverse reproductive endocrinology and infertility spaces, including clinical, ambulatory surgery, laboratory, and research settings, present their experiences using teaming models to adapt team members' thinking, elevate the quality of scientific productivity, and achieve excellence in both patient care and laboratory and clinical outcomes.