RESUMEN
The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathologists. Though artificial intelligence (AI) promises to improve the access and quality of healthcare, the costs of image digitization in pathology and difficulties in deploying AI solutions remain as barriers to real-world use. Here we propose a cost-effective solution: the augmented reality microscope (ARM). The ARM overlays AI-based information onto the current view of the sample in real time, enabling seamless integration of AI into routine workflows. We demonstrate the utility of ARM in the detection of metastatic breast cancer and the identification of prostate cancer, with latency compatible with real-time use. We anticipate that the ARM will remove barriers towards the use of AI designed to improve the accuracy and efficiency of cancer diagnosis.
Asunto(s)
Inteligencia Artificial , Neoplasias de la Mama/diagnóstico , Neoplasias/diagnóstico , Neoplasias de la Próstata/diagnóstico , Neoplasias de la Mama/patología , Femenino , Humanos , Masculino , Microscopía/métodos , Estadificación de Neoplasias , Neoplasias/patología , Neoplasias de la Próstata/patologíaRESUMEN
We have identified novel G protein-coupled receptors (GPCRs) with no introns in the coding region from the human genome sequence: 322 olfactory receptors; 22 taste receptors; 128 registered GPCRs for endogenous ligands; 50 novel GPCR candidates homologous to registered GPCRs for endogenous ligands; and 59 novel GPCR candidates not homologous to registered GPCRs. The total number of GPCRs with and without introns in the human genome was estimated to be approximately 950, of which 500 are odorant or taste receptors and 450 are receptors for endogenous ligands.