Here are six key AI studies that have been published recently:
- “Whose morality? Which rationality? Challenging artificial intelligence as a remedy for the lack of moral enhancement“: As AI becomes more and more integrated into clinical workflows, this study explored the technology’s ability to meet human ethical standards.
- “Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer“: The research team developed a deep learning model to quantify patients’ tumour-stroma ratio, which can help predict outcomes for those with colorectal cancer.
- “A microstructural neural network biomarker for dystonia diagnosis identified by a DystoniaNet deep learning platform“: Researchers developed an AI platform to detect cases of dystonia, for which there is currently no diagnostic test, from an MRI with 98.8 percent accuracy.
- “External evaluation of 3 commercial artificial intelligence algorithms for independent assessment of screening mammograms“: The study assessed three commercially available algorithms designed to detect breast cancer to measure how they performed when used independently as well as in combination with radiologists’ analysis.
- “Multicenter multireader evaluation of an artificial intelligence-based attention mapping system for the detection of prostate cancer with multiparametric MRI“: The research team investigated how AI detection systems compared to multiparametric MRI systems in identifying prostate cancer, finding that the AI system only minimally improved overall sensitivity.
- “A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks“: The study examined 16 convolutional neural networks to determine how efficiently they could use imaging data to improve COVID-19 point-of-care diagnostic and detection tools.
More articles on artificial intelligence:
AI tool gains FDA emergency approval to help treat COVID-19 patients: 4 details
Mount Sinai names new dean of AI, human health: 5 things to know
UCSF teams with Microsoft, others to fast-track AI in healthcare: 5 details
