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Machine learning to detect signatures of disease in liquid biopsies–a user's guide
New technologies that measure sparse molecular biomarkers from easily accessible bodily
fluids (eg blood, urine, and saliva) are revolutionizing disease diagnostics and precision …
fluids (eg blood, urine, and saliva) are revolutionizing disease diagnostics and precision …
[HTML][HTML] Machine learning of Raman spectroscopy data for classifying cancers: a review of the recent literature
Raman Spectroscopy has long been anticipated to augment clinical decision making, such
as classifying oncological samples. Unfortunately, the complexity of Raman data has thus far …
as classifying oncological samples. Unfortunately, the complexity of Raman data has thus far …
Toward a perspectivist turn in ground truthing for predictive computing
Abstract Most current Artificial Intelligence applications are based on supervised Machine
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …
Unintended consequences of machine learning in medicine
Overthepastdecade, machinelearningtechniqueshave made substantial advances in many
domains. In health care, global interest in the potential of machine learning hasincreased; …
domains. In health care, global interest in the potential of machine learning hasincreased; …
The impact of inconsistent human annotations on AI driven clinical decision making
In supervised learning model development, domain experts are often used to provide the
class labels (annotations). Annotation inconsistencies commonly occur when even highly …
class labels (annotations). Annotation inconsistencies commonly occur when even highly …
Cancer diagnosis through IsomiR expression with machine learning method
Background: IsomiR is an isoform of microRNA (miRNA), and its sequences vary from those
of a reference miRNA, which arose with the advencements of deep sequencing, high miRNA …
of a reference miRNA, which arose with the advencements of deep sequencing, high miRNA …
Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review
In the last years, liquid biopsy gained increasing clinical relevance for detecting and
monitoring several cancer types, being minimally invasive, highly informative and replicable …
monitoring several cancer types, being minimally invasive, highly informative and replicable …
Cloud‐based decision support system for the detection and classification of malignant cells in breast cancer using breast cytology images
The advancement of computer‐and internet‐based technologies has transformed the nature
of services in healthcare by using mobile devices in conjunction with cloud computing. The …
of services in healthcare by using mobile devices in conjunction with cloud computing. The …
Deep learning of circulating tumour cells
Circulating tumour cells (CTCs) found in the blood of cancer patients are a promising
biomarker in precision medicine. However, their use is currently hindered by their low …
biomarker in precision medicine. However, their use is currently hindered by their low …
Challenges for machine learning in clinical translation of big data imaging studies
Combining deep learning image analysis methods and large-scale imaging datasets offers
many opportunities to neuroscience imaging and epidemiology. However, despite these …
many opportunities to neuroscience imaging and epidemiology. However, despite these …