This research provides a visual and analytical exploration of technology accessibility in two major hospitals in Madagascar - one in Nosy Be and the other in Antananarivo. Through a collection of photographs and observations, we document the current state of technological resources and their utilization in these healthcare settings. The paper aims to shed light on the challenges and opportunities in integrating technology in healthcare in resource-limited environments, offering insights into how these barriers can be addressed to improve healthcare delivery.

This paper explores the development and potential impact of an open-source clinical drug information (CDI) database, derived from AI-extracted data from SmPC documents. It addresses the current challenges in accessing comprehensive drug information and discusses how an open-source database could revolutionize access to such information, contributing to improved patient outcomes and fostering innovation in healthcare technology.

This paper delves into the complex legal terrain surrounding the access and dissemination of drug information, with a particular focus on the implications of copyright laws and open access principles. It examines the legal barriers that restrict the flow of vital drug information from Summary of Product Characteristics (SmPC) documents to healthcare providers and patients. By analyzing current copyright restrictions and their impact on healthcare technology innovation, the study aims to propose a framework for balancing intellectual property rights with the need for open access to drug information. This exploration seeks to contribute to the broader discussion on how legal frameworks can adapt to the evolving landscape of healthcare information technology, ultimately benefiting public health and patient care.

This research focuses on the development of a novel natural language processing (NLP) algorithm tailored for extracting clinical drug information from Summary of Product Characteristics (SmPC) documents. The study aims to enhance the efficiency and accuracy of drug information retrieval, thereby facilitating better patient education and care. The effectiveness of the algorithm is validated through extensive testing against traditional manual extraction methods.