Although highly successful, the medical R&D model is failing at improving people’s health due to a series of flaws and defects inherent to the model itself. A new collective intelligence, incorporating human and artificial intelligence (AI) could overcome these obstacles. Because AI will play a key role in this new collective intelligence, it is necessary that those involved in healthcare have a general knowledge of how these technologies work. With this comprehensive review, we intend to provide it. A broad-ranging search has been undertaken on institutional and non-institutional websites in order to identify relevant papers, comments and reports. We firstly describe the flaws and defects of the current R&D biomedical model and how the generation of a new collective intelligence will result in a better and wiser medicine through a truly personalized and holistic approach. We, then, discuss the new forms of data collection and data processing and the different types of artificial learning and their specific algorithms. Finally, we review the current uses and applications of AI in the biomedical field and how these can be expanded, as well as the limitations and challenges of applying these new technologies in the medical field. This colossal common effort based on a new collective intelligence will exponentially improve the quality of medical research, resulting in a radical change for the better in the healthcare model. AI, without replacing us, is here to help us achieve the ambitious goal set by the WHO in the Alma Ata declaration of 1978: “Health for All”.
COVID-19 detector: Our tool uses a deep convolutional network to detect and locate radiological signs associated with COVID-19 in frontal chest radiographs, differentiating them from those associated with common bacterial and viral pneumonias. The physician supplies the anonymized radiological image via a cell phone, website, or email to the cloud. The system also generates a heatmap indicating the region of the image where the algorithm detects radiological signs associated with this pathology.