Prospective evaluation of SkinGuard, a deep algorithmic framework for the classification of neoplastic skin lesions

Introduction. Diagnostic errors between nevic lesions and skin tumors are frequent for non-specialist physicians. Therefore, there is a need to create a simple and practical tool based on artificial intelligence to assists them in distinguishing potentially malignant lesions from benign ones, improving early detection of skin cancer. Objective. To evaluate the performance of SkinGuard, an…

El arte de la medicina hipocrática y la IA: un binomio al servicio del paciente

En un mundo en constante cambio y evolución como el nuestro, pocos métodos o doctrinas pueden tener el honor de permanecer vigentes durante más de 2.000 años. Uno de estos excepcionales casos es el método hipocrático, gracias al cual la medicina abandonó la superstición y la magia ejercidas por sacerdotes-médicos en aquella época y se…

Analysis of transcriptomic responses to SARS-CoV-2 reveals plausible defective pathways responsible for increased susceptibility to infection and complications and helps to develop fast-track repositioning of drugs against COVID-19

Background: To understand the transcriptomic response to SARS-CoV-2 infection, is of the utmost importance to design diagnostic tools predicting the severity of the infection. Methods: We have performed a deep sampling analysis of the viral transcriptomic data oriented towards drug repositioning. Using different samplers, the basic principle of this methodology the biological invariance, which means…

Detecting panitumumab/FOLFOX responders in K-Ras wild-type metastatic colorectal cancer through an artificial intelligence-based analytical tool

Background: Patients with K-RAS wild-type (WT) metastatic colorectal cancer (mCRC) are currently considered the optimal candidates for upfront treatment with combinations of chemotherapy and EGFR inhibitors. These combinations significantly extend overall survival (OS) compared to chemotherapy alone. However, a proportion of patients would not achieve this goal. This study has investigated the ability of an…

Use of deep learning frameworks to detect super-responder and super-survivor stage IV squamous non-small-cell lung cancer (NSCLC) patients treated with a gemcitabine and cisplatin combination

Background: Synthetic fingerprints integrate clinical data within computational models allowing the identification of particular clinical subpopulations at a given moment. We here describe a deep learning strategy to detect super-responder and super-survivor patients with squamous NSCLC by setting up synthetic fingerprints and using unsupervised deep learning frameworks (UDLF). Methods: Through www.projectdatasphere.org, we accessed the control…

Predicting disease progression and mortality in metastatic colorectal cancer patients (mCRC) through an artificial intelligence-based analytical tool

Background: Predicting the clinical course of metastatic disease remains a key challenge in CRC. Estimating prognosis of these late-stage patients can avoid undertreatment or overtreatment and also guide the follow-up intensity. This study has investigated the ability of an artificial intelligence-based analytical tool to identify those mCRC patients with high risk of disease progression and…

Deep Neural Frameworks Improve the Accuracy of General Practitioners in the Classification of Pigmented Skin Lesions

This study evaluated whether deep learning frameworks trained in large datasets can help non-dermatologist physicians improve their accuracy in categorizing the seven most common pigmented skin lesions. Open-source skin images were downloaded from the International Skin Imaging Collaboration (ISIC) archive. Different deep neural networks (DNNs) (n = 8) were trained based on a random dataset…

Artificial intelligence: a disruptive tool for a smarter medicine

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…