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A convolutional attention model for predicting response to chemo ...


Machine learning in the prediction of cancer therapy - ScienceDirect

A supervised classification model using a 70-gene signature was developed in 2002 to predict chemotherapy responses in breast cancer [76]. The method was ...

A transformer-based deep learning model for early prediction of ...

A transformer-based DLN was developed using 3D tumor images to predict LNM after NAC. A clinical model was constructed through multivariate ...

NACNet: A Histology Context-aware Transformer Graph Convolution ...

Model for NAC response: We develop the spatial TME graph-based prediction model with the PyTorch framework. The resulting model is trained with ...

Deep learning model based on endoscopic images predicting ...

However, the treatment response varies greatly among individuals, how to select the optimal candidates for neoadjuvant chemoradiotherapy is ...

spatial attention guided deep learning system for prediction of ...

By the maximum voting from patch-level results, our proposed model achieves a 93% patient-level accuracy, outperforming baselines and other state-of-the-art ...

Histology-Based Prediction of Therapy Response to Neoadjuvant ...

Our results show that DL algorithms can predict treatment response to neoadjuvant chemotherapy using WSI with high accuracy even before therapy initiation, ...

Treatment response prediction of neoadjuvant chemotherapy for ...

Finally, the present study constructed another prediction model based on deep learning of clinical responses and colonoscopy images ...

Predicting treatment response in multicenter non-small cell lung ...

We demonstrate that the performance of a FL predictive model, developed by combining convolutional neural networks (CNNs) with data from ...

Chrysovalantis Voutouri, PhD on LinkedIn: A convolutional attention ...

... A convolutional attention model for predicting ...

Predicting the Tumor Microenvironment Composition and ... - medRxiv

Hence, we developed a supervised ML model that incorporates interactions between H&E-inferred TME signatures to predict immunotherapy responders ...

Diagnostic Accuracy of Machine-Learning Models on Predicting ...

From all included ML models, support vector machine demonstrated the best test performance. ML models represent a promising, reliable modality for chemo-brain ...

Predictive Value of Machine Learning for Platinum Chemotherapy ...

Background: Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer.

A convolutional attention model for predicting response to chemo ...

A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models. 从超声弹性成像预测小鼠肿瘤 ...

PUBLICATIONS - Cancer Biophysics Laboratory

A prognostic convolutional attention model for predicting tumor response to chemo-immunotherapy from ultrasound elastography. Communications Medicine. [DOI ...

Using multi-scale convolutional neural network based ... - IEEE Xplore

attention mechanism to assign attention ... deep learning model. Then, the model can be used ... "Predicting treatment response to neoadjuvant chemoradiotherapy in ...

Attention mechanism based multi-sequence MRI fusion improves ...

In summary, this study demonstrated attention mechanism based multi-sequence fusion method was effective for nCRT response prediction in LARC, ...

A convolutional attention model for predicting ... - DataCite Commons

A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models · https://doi.org/10.5281 ...

German Oncology Center on LinkedIn: A convolutional attention ...

A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models - ...

Deep learning model based on multi-lesion and time series CT ...

To develop and validate a deep learning model based on multi-lesion and time series CT images in predicting overall survival (OS) in ...

Machine and Deep Learning Methods for Predicting Immune ...

In our work, we developed several ML and. DL models to predict response to ICB. Our main contributions are three-fold: 1. We propose a model based on gradient.