Abstract
No public abstract is available from the verified source records.
Samvedna Singh, Aman Chandra Kaushik, Shakti Sahi
Abstract
Authors
Institutions
Provenance
crossref
Confidence 100%
ror
Confidence 99%
ror
Confidence 99%
openalex
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Biomarkers as biomedical bioindicators: approaches and techniques for the detection, analysis, and validation of novel biomarkers of diseases
10.3390/pharmaceutics15061630 · 2023
Enhanced deep learning model for personalized cancer treatment
10.1109/access.2022.3209285 · 2022
A random forest based predictor for medical data classification using feature ranking
10.1016/j.imu.2019.100180 · 2019
A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
10.3390/jpm12020309 · 2022
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · 2023
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
10.1186/s13059-020-02015-1 · 2020
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · 2021
Emerging trends in IoT and big data analytics for biomedical and health care technologies
2019
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
10.1001/jama.2017.14585 · 2017
Confidence 95%
datacite
Confidence 0%
Deep learning artificial intelligence predicts homologous recombination deficiency and Platinum response from histologic slides
2024
Deep learning and radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer
2018
Artificial intelligence in early drug discovery enabling precision medicine
10.1080/17460441.2021.1918096 · 2021
Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors
2018
Machine learning for multi-omics data integration in cancer
10.1016/j.isci.2022.103798 · 2022
70-gene signature as an aid to treatment decisions in early-stage breast cancer
10.1056/nejmoa1602253 · 2016
Machine learning for predicting survival of colorectal cancer patients
10.1038/s41598-023-35649-9 · 2023
Machine-learning-based late fusion on multi-omics and multi-scale data for non-small-cell lung cancer diagnosis
10.3390/jpm12040601 · 2022
Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer
10.1186/s12859-020-3356-6 · 2020
Advancing drug discovery via artificial intelligence
10.1016/j.tips.2019.06.004 · 2019
Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges
10.3390/polym12010163 · 2020
A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis
10.1016/j.ymeth.2022.02.011 · 2022
Prediction of all-cause mortality based on stress/rest myocardial perfusion imaging (MPI) using deep learning: a comparison between image and frequency spectra as input
10.3390/jpm12071105 · 2022
Comparative analysis of heart disease prediction using machine learning algorithms
10.1007/978-981-99-1620-7_23 · 2023
Big data analytics for personalized medicine
10.1016/j.copbio.2019.03.004 · 2019
Biomarkers in cancer detection, diagnosis, and prognosis
10.3390/s24010037 · 2024
IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles
10.1093/bioinformatics/btad755 · 2023
A deep learning model to predict a diagnosis of Alzheimer disease by using 18 F-FDG PET of the brain
10.1148/radiol.2018180958 · 2019
Deep phenotyping of Parkinson’s disease
10.3233/jpd-202006 · 2020
Deep learning: new computational modelling techniques for genomics
10.1038/s41576-019-0122-6 · 2019
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · 2017
PADME: a deep learning-based framework for drug-target interaction prediction
2018
A phase I/II trial of concurrent immunotherapy with chemoradiation in locally advanced larynx cancer
10.1002/lio2.780 · 2022
From hype to reality: data science enabling personalized medicine
10.1186/s12916-018-1122-7 · 2018
Systematic identification of genomic markers of drug sensitivity in cancer cells
10.1038/nature11005 · 2012
Precision oncology: an overview
10.1200/jco.2013.49.4799 · 2013
A data-driven approach to predicting successes and failures of clinical trials
10.1016/j.chembiol.2016.07.023 · 2016
The consensus molecular subtypes of colorectal cancer
10.1038/nm.3967 · 2015
A precision medicine framework using artificial intelligence for the identification and confirmation of genomic biomarkers of response to an Alzheimer’s disease therapy: analysis of the blarcamesine (ANAVEX2-73) phase 2a clinical study
10.1002/trc2.12013 · 2020
Innovations in genomics and big data analytics for personalized medicine and health care: a review
10.3390/ijms23094645 · 2022
Artificial intelligence in pancreatic cancer
10.7150/thno.77949 · 2022
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
10.1038/s41588-018-0160-6 · doi-reference
Molecular subtyping of cancer: current status and moving toward clinical applications
10.1093/bib/bby026 · doi-reference
DeepDR: a network-based deep learning approach to in silico drug repositioning
10.1093/bioinformatics/btz418 · doi-reference
Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients
10.1038/nm.4333 · doi-reference
Reinforcement learning strategies in cancer chemotherapy treatments: a review
10.1016/j.cmpb.2022.107280 · doi-reference
Applying artificial intelligence for cancer immunotherapy
10.1016/j.apsb.2021.02.007 · doi-reference
IDrug-target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach
10.1080/07391102.2014.998710 · doi-reference
Estimation of clinical trial success rates and related parameters
10.1093/biostatistics/kxx069 · doi-reference
Accuracy of support-vector machines for diagnosis of Alzheimer’s disease, using volume of brain obtained by structural MRI at Siriraj Hospital
10.3389/fneur.2021.640696 · doi-reference
Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial
10.1007/s10549-017-4509-9 · doi-reference
Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction
10.1038/s41598-022-10358-x · doi-reference
From machine learning to patient outcomes: a comprehensive review of AI in pancreatic cancer
10.3390/diagnostics14020174 · doi-reference
Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review
10.1007/s11030-021-10237-z · doi-reference
Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
10.5114/wo.2014.47136 · doi-reference
Advances in artificial intelligence (AI)-assisted approaches in drug screening
10.1016/j.aichem.2023.100039 · doi-reference
Artificial intelligence in oncology
10.1111/cas.14377 · doi-reference
Precision medicine and the future of cardiovascular diseases: a clinically oriented comprehensive review
10.3390/jcm12051799 · doi-reference
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
10.1007/s11030-021-10326-z · doi-reference
Artificial intelligence and machine learning in precision medicine: a paradigm shift in big data analysis
10.1016/bs.pmbts.2022.03.002 · doi-reference
Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer
10.1038/nature23003 · doi-reference
Machine learning in medicine
10.1056/nejmra1814259 · doi-reference
DrugnomeAI is an ensemble machine-learning framework for predicting druggability of candidate drug targets
10.1038/s42003-022-04245-4 · doi-reference
An immune-related gene signature for predicting neoadjuvant chemoradiotherapy efficacy in rectal carcinoma
10.3389/fimmu.2022.784479 · doi-reference
PLINK: a tool set for whole-genome association and population-based linkage analyses
10.1086/519795 · doi-reference
DeepSynergy: predicting anti-cancer drug synergy with deep learning
10.1093/bioinformatics/btx806 · doi-reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · doi-reference
Artificial intelligence (AI) in personalized medicine: AI-generated personalized therapy regimens based on genetic and medical history: short communication
10.1097/ms9.0000000000001320 · doi-reference
DeepDTA: deep drug-target binding affinity prediction
10.1093/bioinformatics/bty593 · doi-reference
An immunogenic personal neoantigen vaccine for patients with melanoma
10.1038/nature22991 · doi-reference
Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches
10.1186/s13014-019-1345-6 · doi-reference
Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials
10.1016/s2589-7500(22)00170-4 · doi-reference
BRAF alterations as therapeutic targets in non-small-cell lung cancer
10.1097/jto.0000000000000644 · doi-reference
Predicting the impact of single nucleotide variants on splicing via sequence‐based deep neural networks and genomic features
10.1002/humu.23794 · doi-reference
The prognostic impact of consensus molecular subtypes (CMS) and its predictive effects for bevacizumab benefit in metastatic colorectal cancer: molecular analysis of the AGITG MAX clinical trial
10.1093/annonc/mdy410 · doi-reference
A scoping review of artificial intelligence-based methods for diabetes risk prediction
10.1038/s41746-023-00933-5 · doi-reference
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties
10.1371/journal.pone.0061318 · doi-reference
Advancing precision medicine: a review of innovative in silico approaches for drug development
10.3390/pharmaceutics16030332 · doi-reference
The Parkinson’s progression markers initiative (PPMI) – establishing a PD biomarker cohort
10.1002/acn3.644 · doi-reference
The role of CYP2D6 polymorphisms in determining response to tamoxifen in metastatic breast cancer patients: review and Egyptian experience
10.31557/apjcp.2020.21.12.3619 · doi-reference
A case study for a big data and machine learning platform to improve medical decision support in population health management
10.3390/a13040102 · doi-reference