AIMC Topic: Humans

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Emulating complex simulations by machine learning methods.

BMC bioinformatics
BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and ...

Application of Neural Network Algorithm Based on Principal Component Image Analysis in Band Expansion of College English Listening.

Computational intelligence and neuroscience
With the development of information technology, band expansion technology is gradually applied to college English listening teaching. This technology aims to recover broadband speech signals from narrowband speech signals with a limited frequency ban...

Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway.

PloS one
Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and utility as biomarkers remains poorly understood. In this study, we analysed 505 PTC patients by employ...

Treatment selection using prototyping in latent-space with application to depression treatment.

PloS one
Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. W...

Study on augmented reality for robotic surgery bedside assistants.

Journal of robotic surgery
Robotic surgery bedside assistants play an important role in robotic procedures by performing intra-corporeal tasks while accommodating the physical presence of the robot. We hypothesized that an augmented reality headset enabling 3D intra-corporeal ...

Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.

Nature biomedical engineering
Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with gliob...

Integration of Deep Learning Radiomics and Counts of Circulating Tumor Cells Improves Prediction of Outcomes of Early Stage NSCLC Patients Treated With Stereotactic Body Radiation Therapy.

International journal of radiation oncology, biology, physics
PURPOSE: We develop a deep learning (DL) radiomics model and integrate it with circulating tumor cell (CTC) counts as a clinically useful prognostic marker for predicting recurrence outcomes of early-stage (ES) non-small cell lung cancer (NSCLC) pati...

Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From convolutional neural networks to visual transformers.

Computers in biology and medicine
Cervical cancer is a very common and fatal type of cancer in women. Cytopathology images are often used to screen for this cancer. Given that there is a possibility that many errors can occur during manual screening, a computer-aided diagnosis system...

Artificial Intelligence Assessment of Renal Scarring (AIRS Study).

Kidney360
BACKGROUND: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans.