Research graph
References from Artificial intelligence-driven personalized medicine and biomarker discovery. Local targets link to admitted publications; unresolved targets remain external evidence.
Biomarkers as biomedical bioindicators: approaches and techniques for the detection, analysis, and validation of novel biomarkers of diseases
10.3390/pharmaceutics15061630 · 2023 · External reference
Enhanced deep learning model for personalized cancer treatment
10.1109/access.2022.3209285 · 2022 · External reference
A random forest based predictor for medical data classification using feature ranking
10.1016/j.imu.2019.100180 · 2019 · External reference
A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
10.3390/jpm12020309 · 2022 · External reference
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · 2023 · External reference
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
10.1186/s13059-020-02015-1 · 2020 · External reference
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · 2021 · External reference
Emerging trends in IoT and big data analytics for biomedical and health care technologies
2019 · External reference
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
10.1001/jama.2017.14585 · 2017 · External reference
Deep learning artificial intelligence predicts homologous recombination deficiency and Platinum response from histologic slides
2024 · External reference
Deep learning and radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer
2018 · External reference
Artificial intelligence in early drug discovery enabling precision medicine
10.1080/17460441.2021.1918096 · 2021 · External reference
Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors
2018 · External reference
Machine learning for multi-omics data integration in cancer
10.1016/j.isci.2022.103798 · 2022 · External reference
70-gene signature as an aid to treatment decisions in early-stage breast cancer
10.1056/nejmoa1602253 · 2016 · External reference
Machine learning for predicting survival of colorectal cancer patients
10.1038/s41598-023-35649-9 · 2023 · External reference
Machine-learning-based late fusion on multi-omics and multi-scale data for non-small-cell lung cancer diagnosis
10.3390/jpm12040601 · 2022 · External reference
Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer
10.1186/s12859-020-3356-6 · 2020 · External reference
Advancing drug discovery via artificial intelligence
10.1016/j.tips.2019.06.004 · 2019 · External reference
Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges
10.3390/polym12010163 · 2020 · External reference
A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis
10.1016/j.ymeth.2022.02.011 · 2022 · External reference
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 · External reference
Comparative analysis of heart disease prediction using machine learning algorithms
10.1007/978-981-99-1620-7_23 · 2023 · External reference
Big data analytics for personalized medicine
10.1016/j.copbio.2019.03.004 · 2019 · External reference
Biomarkers in cancer detection, diagnosis, and prognosis
10.3390/s24010037 · 2024 · External reference
IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles
10.1093/bioinformatics/btad755 · 2023 · External reference
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 · External reference
Deep phenotyping of Parkinson’s disease
10.3233/jpd-202006 · 2020 · External reference
Deep learning: new computational modelling techniques for genomics
10.1038/s41576-019-0122-6 · 2019 · External reference
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · 2017 · External reference
PADME: a deep learning-based framework for drug-target interaction prediction
2018 · External reference
A phase I/II trial of concurrent immunotherapy with chemoradiation in locally advanced larynx cancer
10.1002/lio2.780 · 2022 · External reference
From hype to reality: data science enabling personalized medicine
10.1186/s12916-018-1122-7 · 2018 · External reference
Systematic identification of genomic markers of drug sensitivity in cancer cells
10.1038/nature11005 · 2012 · External reference
Precision oncology: an overview
10.1200/jco.2013.49.4799 · 2013 · External reference
A data-driven approach to predicting successes and failures of clinical trials
10.1016/j.chembiol.2016.07.023 · 2016 · External reference
The consensus molecular subtypes of colorectal cancer
10.1038/nm.3967 · 2015 · External reference
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 · External reference
Innovations in genomics and big data analytics for personalized medicine and health care: a review
10.3390/ijms23094645 · 2022 · External reference
Artificial intelligence in pancreatic cancer
10.7150/thno.77949 · 2022 · External reference
Open source machine-learning algorithms for the prediction of optimal cancer drug therapies
10.1371/journal.pone.0186906 · 2017 · External reference
Integrative analysis of gene expression profiles of substantia nigra identifies potential diagnosis biomarkers in Parkinson’s disease
2024 · External reference
Applications of support vector machine (SVM) learning in cancer genomics
2018 · External reference
Chronic kidney disease prediction based on machine learning algorithms
2023 · External reference
AutoPrognosis 2.0: democratizing diagnostic and prognostic modeling in healthcare with automated machine learning
10.1371/journal.pdig.0000276 · 2023 · External reference
Precision medicine in cardiovascular therapeutics: evaluating the role of pharmacogenetic analysis prior to drug treatment
10.1111/joim.13772 · 2024 · External reference
Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma
10.1186/s12885-022-09352-3 · 2022 · External reference
Autosurv: interpretable deep learning framework for cancer survival analysis incorporating clinical and multi-omics data
10.1038/s41698-023-00494-6 · 2024 · External reference
The impact of the Alzheimer’s disease neuroimaging initiative 2: what role do public‐private partnerships have in pushing the boundaries of clinical and basic science research on Alzheimer’s disease?
10.1016/j.jalz.2015.05.006 · 2015 · External reference
Position classification of the endotracheal tube with automatic segmentation of the trachea and the tube on plain chest radiography using deep convolutional neural network
10.3390/jpm12091363 · 2022 · External reference
PandaOmics: an AI-driven platform for therapeutic target and biomarker discovery
10.1021/acs.jcim.3c01619 · 2024 · External reference
Recent advancements using machine learning & deep learning approaches for diabetes detection: a systematic review
10.1016/j.prime.2024.100661 · 2024 · External reference
Globally ncRNAs expression profiling of TNBC and screening of functional lncRNA
10.3389/fbioe.2020.523127 · 2021 · External reference
Robust biomarker screening using spares learning approach for liver cancer prognosis
10.3389/fbioe.2020.00241 · 2020 · External reference
Machine learning-driven exploration of drug therapies for triple-negative breast cancer treatment
10.3389/fmolb.2023.1215204 · 2023 · External reference
Artificial intelligence for diabetes: enhancing prevention, diagnosis, and effective management
10.1016/j.cmpbup.2024.100141 · 2024 · External reference
The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care
10.1038/s41591-018-0213-5 · 2018 · External reference
Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm
10.3389/frai.2023.1227091 · 2023 · External reference
Predicting drug response and synergy using a deep learning model of human cancer cells
10.1016/j.ccell.2020.09.014 · 2020 · External reference
Predicting drug response and synergy using a deep learning model of human cancer cells
10.1016/j.ccell.2020.09.014 · 2020 · External reference
A robust deep learning platform to predict CD8+ T-cell epitopes
2022 · External reference
Big data for precision medicine
10.15302/j-eng-2015075 · 2015 · External reference
AdaMedGraph: adaboosting graph neural networks for personalized medicine
2023 · External reference
Predicting drug activity against cancer cells by random forest models based on minimal genomic information and chemical properties
10.1371/journal.pone.0219774 · 2019 · External reference
A survey on deep learning in medical image analysis
10.1016/j.media.2017.07.005 · 2017 · External reference
A case study for a big data and machine learning platform to improve medical decision support in population health management
10.3390/a13040102 · 2020 · External reference
Unresolved reference
2021 · External 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 · 2020 · External reference
The Parkinson’s progression markers initiative (PPMI) – establishing a PD biomarker cohort
10.1002/acn3.644 · 2018 · External reference
Advancing precision medicine: a review of innovative in silico approaches for drug development
10.3390/pharmaceutics16030332 · 2024 · External reference
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties
10.1371/journal.pone.0061318 · 2013 · External reference
A scoping review of artificial intelligence-based methods for diabetes risk prediction
10.1038/s41746-023-00933-5 · 2023 · External 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 · 2018 · External reference
Predicting the impact of single nucleotide variants on splicing via sequence‐based deep neural networks and genomic features
10.1002/humu.23794 · 2019 · External reference
BRAF alterations as therapeutic targets in non-small-cell lung cancer
10.1097/jto.0000000000000644 · 2015 · External 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 · 2022 · External reference
Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches
10.1186/s13014-019-1345-6 · 2019 · External reference
An immunogenic personal neoantigen vaccine for patients with melanoma
10.1038/nature22991 · 2017 · External reference
DeepDTA: deep drug-target binding affinity prediction
10.1093/bioinformatics/bty593 · 2018 · External reference
Deep learning opens new horizons in personalized medicine (Review)
2019 · External reference
Artificial intelligence (AI) in personalized medicine: AI-generated personalized therapy regimens based on genetic and medical history: short communication
10.1097/ms9.0000000000001320 · 2023 · External reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · 2021 · External reference
DeepSynergy: predicting anti-cancer drug synergy with deep learning
10.1093/bioinformatics/btx806 · 2018 · External reference
PLINK: a tool set for whole-genome association and population-based linkage analyses
10.1086/519795 · 2007 · External reference
An immune-related gene signature for predicting neoadjuvant chemoradiotherapy efficacy in rectal carcinoma
10.3389/fimmu.2022.784479 · 2022 · External reference
DrugnomeAI is an ensemble machine-learning framework for predicting druggability of candidate drug targets
10.1038/s42003-022-04245-4 · 2022 · External reference
Machine learning in medicine
10.1056/nejmra1814259 · 2019 · External reference
Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer
10.1038/nature23003 · 2017 · External reference
Artificial intelligence and machine learning in precision medicine: a paradigm shift in big data analysis
10.1016/bs.pmbts.2022.03.002 · 2022 · External reference
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
10.1007/s11030-021-10326-z · 2022 · External reference
Precision medicine and the future of cardiovascular diseases: a clinically oriented comprehensive review
10.3390/jcm12051799 · 2023 · External reference
Artificial intelligence in oncology
10.1111/cas.14377 · 2020 · External reference
Advances in artificial intelligence (AI)-assisted approaches in drug screening
10.1016/j.aichem.2023.100039 · 2024 · External reference
Interpretable deep learning for improving cancer patient survival based on personal transcriptomes
2023 · External reference
Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
10.5114/wo.2014.47136 · 2015 · External reference
Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review
10.1007/s11030-021-10237-z · 2021 · External reference
From machine learning to patient outcomes: a comprehensive review of AI in pancreatic cancer
10.3390/diagnostics14020174 · 2024 · External reference
Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction
10.1038/s41598-022-10358-x · 2022 · External 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 · 2018 · External 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 · 2021 · External reference
Estimation of clinical trial success rates and related parameters
10.1093/biostatistics/kxx069 · 2019 · External 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 · 2015 · External reference
Applying artificial intelligence for cancer immunotherapy
10.1016/j.apsb.2021.02.007 · 2021 · External reference
Reinforcement learning strategies in cancer chemotherapy treatments: a review
10.1016/j.cmpb.2022.107280 · 2023 · External reference
Multi-domain translation by learning uncoupled autoencoders
2019 · External reference
Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients
10.1038/nm.4333 · 2017 · External reference
DeepDR: a network-based deep learning approach to in silico drug repositioning
10.1093/bioinformatics/btz418 · 2019 · External reference
Molecular subtyping of cancer: current status and moving toward clinical applications
10.1093/bib/bby026 · 2019 · External reference
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
10.1038/s41588-018-0160-6 · 2018 · External reference
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
10.1001/jama.2017.14585 · ExternalCitation · doi-reference
The Parkinson’s progression markers initiative (PPMI) – establishing a PD biomarker cohort
10.1002/acn3.644 · ExternalCitation · doi-reference
Predicting the impact of single nucleotide variants on splicing via sequence‐based deep neural networks and genomic features
10.1002/humu.23794 · ExternalCitation · doi-reference
A phase I/II trial of concurrent immunotherapy with chemoradiation in locally advanced larynx cancer
10.1002/lio2.780 · ExternalCitation · doi-reference
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 · ExternalCitation · doi-reference
Comparative analysis of heart disease prediction using machine learning algorithms
10.1007/978-981-99-1620-7_23 · ExternalCitation · 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 · ExternalCitation · 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 · ExternalCitation · doi-reference
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
10.1007/s11030-021-10326-z · ExternalCitation · doi-reference
Artificial intelligence and machine learning in precision medicine: a paradigm shift in big data analysis
10.1016/bs.pmbts.2022.03.002 · ExternalCitation · doi-reference
Advances in artificial intelligence (AI)-assisted approaches in drug screening
10.1016/j.aichem.2023.100039 · ExternalCitation · doi-reference
Applying artificial intelligence for cancer immunotherapy
10.1016/j.apsb.2021.02.007 · ExternalCitation · doi-reference
Predicting drug response and synergy using a deep learning model of human cancer cells
10.1016/j.ccell.2020.09.014 · ExternalCitation · doi-reference
A data-driven approach to predicting successes and failures of clinical trials
10.1016/j.chembiol.2016.07.023 · ExternalCitation · doi-reference
Reinforcement learning strategies in cancer chemotherapy treatments: a review
10.1016/j.cmpb.2022.107280 · ExternalCitation · doi-reference
Artificial intelligence for diabetes: enhancing prevention, diagnosis, and effective management
10.1016/j.cmpbup.2024.100141 · ExternalCitation · doi-reference
Big data analytics for personalized medicine
10.1016/j.copbio.2019.03.004 · ExternalCitation · doi-reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · ExternalCitation · doi-reference
A random forest based predictor for medical data classification using feature ranking
10.1016/j.imu.2019.100180 · ExternalCitation · doi-reference
Machine learning for multi-omics data integration in cancer
10.1016/j.isci.2022.103798 · ExternalCitation · doi-reference
The impact of the Alzheimer’s disease neuroimaging initiative 2: what role do public‐private partnerships have in pushing the boundaries of clinical and basic science research on Alzheimer’s disease?
10.1016/j.jalz.2015.05.006 · ExternalCitation · doi-reference
A survey on deep learning in medical image analysis
10.1016/j.media.2017.07.005 · ExternalCitation · doi-reference
Recent advancements using machine learning & deep learning approaches for diabetes detection: a systematic review
10.1016/j.prime.2024.100661 · ExternalCitation · doi-reference
Advancing drug discovery via artificial intelligence
10.1016/j.tips.2019.06.004 · ExternalCitation · doi-reference
A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis
10.1016/j.ymeth.2022.02.011 · ExternalCitation · 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 · ExternalCitation · doi-reference
PandaOmics: an AI-driven platform for therapeutic target and biomarker discovery
10.1021/acs.jcim.3c01619 · ExternalCitation · doi-reference
Systematic identification of genomic markers of drug sensitivity in cancer cells
10.1038/nature11005 · ExternalCitation · doi-reference
Dermatologist-level classification of skin cancer with deep neural networks
10.1038/nature21056 · ExternalCitation · doi-reference
An immunogenic personal neoantigen vaccine for patients with melanoma
10.1038/nature22991 · ExternalCitation · doi-reference
Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer
10.1038/nature23003 · ExternalCitation · doi-reference
The consensus molecular subtypes of colorectal cancer
10.1038/nm.3967 · ExternalCitation · doi-reference
Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients
10.1038/nm.4333 · ExternalCitation · doi-reference
Deep learning: new computational modelling techniques for genomics
10.1038/s41576-019-0122-6 · ExternalCitation · doi-reference
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
10.1038/s41588-018-0160-6 · ExternalCitation · doi-reference
The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care
10.1038/s41591-018-0213-5 · ExternalCitation · doi-reference
Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction
10.1038/s41598-022-10358-x · ExternalCitation · doi-reference
Machine learning for predicting survival of colorectal cancer patients
10.1038/s41598-023-35649-9 · ExternalCitation · doi-reference
Autosurv: interpretable deep learning framework for cancer survival analysis incorporating clinical and multi-omics data
10.1038/s41698-023-00494-6 · ExternalCitation · doi-reference
A scoping review of artificial intelligence-based methods for diabetes risk prediction
10.1038/s41746-023-00933-5 · ExternalCitation · doi-reference
DrugnomeAI is an ensemble machine-learning framework for predicting druggability of candidate drug targets
10.1038/s42003-022-04245-4 · ExternalCitation · doi-reference
70-gene signature as an aid to treatment decisions in early-stage breast cancer
10.1056/nejmoa1602253 · ExternalCitation · doi-reference
Machine learning in medicine
10.1056/nejmra1814259 · ExternalCitation · 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 · ExternalCitation · doi-reference
Artificial intelligence in early drug discovery enabling precision medicine
10.1080/17460441.2021.1918096 · ExternalCitation · doi-reference
PLINK: a tool set for whole-genome association and population-based linkage analyses
10.1086/519795 · ExternalCitation · 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 · ExternalCitation · doi-reference
Molecular subtyping of cancer: current status and moving toward clinical applications
10.1093/bib/bby026 · ExternalCitation · doi-reference
IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles
10.1093/bioinformatics/btad755 · ExternalCitation · doi-reference
DeepSynergy: predicting anti-cancer drug synergy with deep learning
10.1093/bioinformatics/btx806 · ExternalCitation · doi-reference
DeepDTA: deep drug-target binding affinity prediction
10.1093/bioinformatics/bty593 · ExternalCitation · doi-reference
DeepDR: a network-based deep learning approach to in silico drug repositioning
10.1093/bioinformatics/btz418 · ExternalCitation · doi-reference
Estimation of clinical trial success rates and related parameters
10.1093/biostatistics/kxx069 · ExternalCitation · doi-reference
BRAF alterations as therapeutic targets in non-small-cell lung cancer
10.1097/jto.0000000000000644 · ExternalCitation · 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 · ExternalCitation · doi-reference
Enhanced deep learning model for personalized cancer treatment
10.1109/access.2022.3209285 · ExternalCitation · doi-reference
Artificial intelligence in oncology
10.1111/cas.14377 · ExternalCitation · doi-reference
Precision medicine in cardiovascular therapeutics: evaluating the role of pharmacogenetic analysis prior to drug treatment
10.1111/joim.13772 · ExternalCitation · doi-reference
A deep learning model to predict a diagnosis of Alzheimer disease by using 18 F-FDG PET of the brain
10.1148/radiol.2018180958 · ExternalCitation · doi-reference
Robust pathway sampling in phenotype prediction. Application to triple negative breast cancer
10.1186/s12859-020-3356-6 · ExternalCitation · doi-reference
Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma
10.1186/s12885-022-09352-3 · ExternalCitation · doi-reference
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · ExternalCitation · doi-reference
From hype to reality: data science enabling personalized medicine
10.1186/s12916-018-1122-7 · ExternalCitation · doi-reference
Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches
10.1186/s13014-019-1345-6 · ExternalCitation · doi-reference
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
10.1186/s13059-020-02015-1 · ExternalCitation · doi-reference
Precision oncology: an overview
10.1200/jco.2013.49.4799 · ExternalCitation · doi-reference
AutoPrognosis 2.0: democratizing diagnostic and prognostic modeling in healthcare with automated machine learning
10.1371/journal.pdig.0000276 · ExternalCitation · doi-reference
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties
10.1371/journal.pone.0061318 · ExternalCitation · doi-reference
Open source machine-learning algorithms for the prediction of optimal cancer drug therapies
10.1371/journal.pone.0186906 · ExternalCitation · doi-reference
Predicting drug activity against cancer cells by random forest models based on minimal genomic information and chemical properties
10.1371/journal.pone.0219774 · ExternalCitation · doi-reference
Big data for precision medicine
10.15302/j-eng-2015075 · ExternalCitation · 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 · ExternalCitation · doi-reference
Deep phenotyping of Parkinson’s disease
10.3233/jpd-202006 · ExternalCitation · doi-reference
Robust biomarker screening using spares learning approach for liver cancer prognosis
10.3389/fbioe.2020.00241 · ExternalCitation · doi-reference
Globally ncRNAs expression profiling of TNBC and screening of functional lncRNA
10.3389/fbioe.2020.523127 · ExternalCitation · doi-reference
An immune-related gene signature for predicting neoadjuvant chemoradiotherapy efficacy in rectal carcinoma
10.3389/fimmu.2022.784479 · ExternalCitation · doi-reference
Machine learning-driven exploration of drug therapies for triple-negative breast cancer treatment
10.3389/fmolb.2023.1215204 · ExternalCitation · 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 · ExternalCitation · doi-reference
Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm
10.3389/frai.2023.1227091 · ExternalCitation · 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 · ExternalCitation · doi-reference
From machine learning to patient outcomes: a comprehensive review of AI in pancreatic cancer
10.3390/diagnostics14020174 · ExternalCitation · doi-reference
Innovations in genomics and big data analytics for personalized medicine and health care: a review
10.3390/ijms23094645 · ExternalCitation · doi-reference
Precision medicine and the future of cardiovascular diseases: a clinically oriented comprehensive review
10.3390/jcm12051799 · ExternalCitation · doi-reference
A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
10.3390/jpm12020309 · ExternalCitation · doi-reference
Machine-learning-based late fusion on multi-omics and multi-scale data for non-small-cell lung cancer diagnosis
10.3390/jpm12040601 · ExternalCitation · doi-reference
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 · ExternalCitation · doi-reference
Position classification of the endotracheal tube with automatic segmentation of the trachea and the tube on plain chest radiography using deep convolutional neural network
10.3390/jpm12091363 · ExternalCitation · doi-reference
Biomarkers as biomedical bioindicators: approaches and techniques for the detection, analysis, and validation of novel biomarkers of diseases
10.3390/pharmaceutics15061630 · ExternalCitation · doi-reference
Advancing precision medicine: a review of innovative in silico approaches for drug development
10.3390/pharmaceutics16030332 · ExternalCitation · doi-reference
Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges
10.3390/polym12010163 · ExternalCitation · doi-reference
Biomarkers in cancer detection, diagnosis, and prognosis
10.3390/s24010037 · ExternalCitation · doi-reference
Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
10.5114/wo.2014.47136 · ExternalCitation · doi-reference
Artificial intelligence in pancreatic cancer
10.7150/thno.77949 · ExternalCitation · doi-reference
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · ExternalCitation · doi-reference
