In brain imaging, decoding is widely used to infer relationships between brain and cognition, or to craft brain-imaging biomarkers of pathologies. Yet, standard decoding procedures do not come with statistical guarantees, and thus do not give confide...
Computer methods and programs in biomedicine
Mar 12, 2021
BACKGROUND AND OBJECTIVES: Cerebral microbleeds (CMBs) are cerebral small vascular diseases and are often used to diagnose symptoms such as stroke and dementia. Manual detection of cerebral microbleeds is a time-consuming and error-prone task, so the...
Computer methods and programs in biomedicine
Mar 12, 2021
BACKGROUND AND OBJECTIVE: Colon cancer is a fatal disease, and a comprehensive understanding of the tumor microenvironment (TME) could lead to better risk stratification, prognosis prediction, and therapy management. In this paper, we focused on the ...
The accuracy of brain age estimates from magnetic resonance (MR) images has improved with the advent of deep learning artificial intelligence (AI) models. However, most previous studies on predicting age emphasized aging from childhood to adulthood a...
Computer methods and programs in biomedicine
Mar 12, 2021
BACKGROUND: Despite the importance of stroke volume readings in understanding the work of the cardiovascular system in patients, its routine daily measurement outside of a hospital in the absence of special equipment presents a problem for a comprehe...
International journal of computer assisted radiology and surgery
Mar 12, 2021
PURPOSE: By integrating locally operated surgical assistant robots in a sterilized area, a surgeon can perform safe robotically assisted laparoscopic solo surgery while controlling a laparoscope-holding robot and a forceps robot. At present, there is...
OBJECTIVES: This study aimed to establish a machine learning prediction model that can be used to predict bone metastasis (BM) in patients with newly diagnosed thyroid cancer (TC).
International journal of molecular sciences
Mar 12, 2021
The exponential growth of biomedical data in recent years has urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research. By enabling the automatic feature extraction, selection, and ge...
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