Priyanka Vasanthakumari
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View article: Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting
Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting Open
Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experim…
View article: The Hallmarks of Predictive Oncology
The Hallmarks of Predictive Oncology Open
The rapid evolution of machine learning has led to a proliferation of sophisticated models for predicting therapeutic responses in cancer. While many of these show promise in research, standards for clinical evaluation and adoption are lac…
View article: Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data Open
Cancer drug response prediction (DRP) models present a promising approach towards precision oncology, tailoring treatments to individual patient profiles. While deep learning (DL) methods have shown great potential in this area, models tha…
View article: Variational and Explanatory Neural Networks for Encoding Cancer Profiles and Predicting Drug Responses
Variational and Explanatory Neural Networks for Encoding Cancer Profiles and Predicting Drug Responses Open
Human cancers present a significant public health challenge and require the discovery of novel drugs through translational research. Transcriptomics profiling data that describes molecular activities in tumors and cancer cell lines are wid…
View article: Pixel-level classification of pigmented skin cancer lesions using multispectral autofluorescence lifetime dermoscopy imaging
Pixel-level classification of pigmented skin cancer lesions using multispectral autofluorescence lifetime dermoscopy imaging Open
There is no clinical tool available to primary care physicians or dermatologists that could provide objective identification of suspicious skin cancer lesions. Multispectral autofluorescence lifetime imaging (maFLIM) dermoscopy enables lab…
View article: Data Imbalance in Drug Response Prediction - Multi-Objective Optimization Approach in Deep Learning Setting
Data Imbalance in Drug Response Prediction - Multi-Objective Optimization Approach in Deep Learning Setting Open
Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly exper-i…
View article: A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening
A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening Open
It is well-known that cancers of the same histology type can respond differently to a treatment. Thus, computational drug response prediction is of paramount importance for both preclinical drug screening studies and clinical treatment des…
View article: Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models
Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models Open
Cancer is a heterogeneous disease in that tumors of the same histology type can respond differently to a treatment. Anti-cancer drug response prediction is of paramount importance for both drug development and patient treatment design. Alt…
View article: Influencing factors on false positive rates when classifying tumor cell line response to drug treatment
Influencing factors on false positive rates when classifying tumor cell line response to drug treatment Open
Informed selection of drug candidates for laboratory experimentation provides an efficient means of identifying suitable anti-cancer treatments. The advancement of artificial intelligence has led to the development of computational models …
View article: Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning
Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning Open
Simple classification ML models based on time-resolved (biexponential and phasor) autofluorescence global features extracted from maFLIM dermoscopy images have the potential to provide objective discrimination of malignant from benign pigm…