Authors: Oiva, Mila, Mukhina, Ksenia, Zemaityte, Vejune, Karjus, Andres, Tamm, Mikhail, Ohm, Tillmann, Mets, Mark, Chávez Heras, Daniel, Canet Sola, Mar, Juht, Helena Hanna, Schich, Maximilian
Superior Title: Oiva , M , Mukhina , K , Zemaityte , V , Karjus , A , Tamm , M , Ohm , T , Mets , M , Chávez Heras , D , Canet Sola , M , Juht , H H & Schich , M 2024 , ' A framework for the analysis of historical newsreels ' , Humanities and Social Sciences Communications , vol. 11 , no. 1 , 530 . https://doi.org/10.1057/s41599-024-02886-w
Subject Terms: Computational aesthetics, computational analysis, Machine learning and Artificial intelligence (AI), Computer vision, film and media studies, Film archives
Authors: Marshall, Iain J., Trikalinos, Thomas A., Soboczenski, Frank, Yun, Hye Sun, Kell, Gregory, Marshall, Rachel, Wallace, Byron C.
Superior Title: Marshall , I J , Trikalinos , T A , Soboczenski , F , Yun , H S , Kell , G , Marshall , R & Wallace , B C 2023 , ' In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving ' , Journal of Clinical Epidemiology , vol. 153 , pp. 26-33 . https://doi.org/10.1016/j.jclinepi.2022.08.013
Subject Terms: Artificial intelligence, Evidence based medicine, Living systematic reviews, Machine learning, Natural language processing, Systematic reviews
Authors: Marriott, Heather, Kabiljo, Renata, Hunt, Guy, Al Khleifat, Ahmad, Jones, Ashley, Troakes, Claire, Dobson, Richard, Al-Chalabi, Ammar, Iacoangeli, Alfredo
Superior Title: Marriott , H , Kabiljo , R , Hunt , G , Al Khleifat , A , Jones , A , Troakes , C , Dobson , R , Al-Chalabi , A & Iacoangeli , A 2023 , ' Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data ' , Acta Neuropathologica Communications , vol. 11 , no. 1 , 208 . https://doi.org/10.1186/s40478-023-01686-8
Subject Terms: amyotrophic lateral sclerosis, Unsupervised and supervised machine learning, Precision medicine, Transcriptomics, Patient stratification, Biomarkers
Authors: Ranson, Janice M., Bucholc, Magda, Lyall, Donald, Newby, Danielle, Winchester, Laura, Oxtoby, Neil P., Veldsman, Michele, Rittman, Timothy, Marzi, Sarah, Skene, Nathan, Al Khleifat, Ahmad, Foote, Isabelle F., Orgeta, Vasiliki, Kormilitzin, Andrey, Lourida, Ilianna, Llewellyn, David J.
Superior Title: Ranson , J M , Bucholc , M , Lyall , D , Newby , D , Winchester , L , Oxtoby , N P , Veldsman , M , Rittman , T , Marzi , S , Skene , N , Al Khleifat , A , Foote , I F , Orgeta , V , Kormilitzin , A , Lourida , I & Llewellyn , D J 2023 , ' Harnessing the potential of machine learning and artificial intelligence for dementia research ' , Brain Informatics , vol. 10 , no. 1 , 6 . https://doi.org/10.1186/s40708-022-00183-3
Subject Terms: Animal models, Artificial intelligence, Dementia, Drug discovery, Genetics, iPSC, Machine learning, Neuroimaging, Prevention
Authors: Lano, Kevin, Xue, Qiaomu
Superior Title: Lano , K & Xue , Q 2023 , ' Code Generation by Example Using Symbolic Machine Learning ' , SN Computer Science , vol. 4 , no. 2 , 170 , pp. 1-23 . https://doi.org/10.1007/s42979-022-01573-4
Subject Terms: Code generation, model-driven engineering, symbolic machine learning
Superior Title: Nassef , O , Sun , W , Purmehdi , H , Tatipamula , M & Mahmoodi , T 2022 , ' A survey : Distributed Machine Learning for 5G and beyond ' , COMPUTER NETWORKS , vol. 207 , 108820 . https://doi.org/10.1016/j.comnet.2022.108820
Subject Terms: 5G networks, Distributed inference, Distributed machine learning, Latency, Machine Learning
Superior Title: Nassef , O , Sun , W , Purmehdi , H , Tatipamula , M & Mahmoodi , T 2022 , ' A survey : Distributed Machine Learning for 5G and beyond ' , COMPUTER NETWORKS , vol. 207 , 108820 . https://doi.org/10.1016/j.comnet.2022.108820
Subject Terms: 5G networks, Distributed inference, Distributed machine learning, Latency, Machine Learning
Availability:
https://doi.org/10.1016/j.comnet.2022.108820
https://kclpure.kcl.ac.uk/portal/en/publications/a-survey(3fdca4a0-dcb3-4817-a03a-51a1d8d990e2).html
http://www.scopus.com/inward/record.url?scp=85125137800&partnerID=8YFLogxK
Authors: Walter, Nina, Wenzel, Julian, Haas, Shalaila S., Squarcina, Letizia, Bonivento, Carolina, Ruef, Anne, Dwyer, Dominic, Lichtenstein, Theresa, Bastrük, Öznur, Stainton, Alexandra, Antonucci, Linda A., Brambilla, Paolo, Wood, Stephen J., Upthegrove, Rachel, Borgwardt, Stefan, Lencer, Rebekka, Meisenzahl, Eva, Salokangas, Raimo K.R., Pantelis, Christos, Bertolino, Alessandro, Koutsouleris, Nikolaos, Kambeitz, Joseph, Kambeitz-Ilankovic, Lana
Superior Title: Walter , N , Wenzel , J , Haas , S S , Squarcina , L , Bonivento , C , Ruef , A , Dwyer , D , Lichtenstein , T , Bastrük , Ö , Stainton , A , Antonucci , L A , Brambilla , P , Wood , S J , Upthegrove , R , Borgwardt , S , Lencer , R , Meisenzahl , E , Salokangas , R K R , Pantelis , C , Bertolino , A , Koutsouleris , N , Kambeitz , J & Kambeitz-Ilankovic , L 2024 , ' ....
Subject Terms: Social functioning, Recent onset psychosis, Social cognitive training, Machine learning, Treatment response
Superior Title: Siegert , R J , Narayanan , A & Turner-Stokes , L 2022 , ' Prediction of emergence from prolonged disorders of consciousness from measures within the UK rehabilitation outcomes collaborative database : a multicentre analysis using machine learning ' , Disability and Rehabilitation . https://doi.org/10.1080/09638288.2022.2114017
Subject Terms: artificial neural networks, logistic regression, machine learning, outcomes, PDOC, prediction, Prolonged disorders of consciousness, vegetative or minimally conscious states
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https://doi.org/10.1080/09638288.2022.2114017
https://kclpure.kcl.ac.uk/portal/en/publications/bfcd91a0-532d-47e6-ad32-7e1ad04b36a5
https://kclpure.kcl.ac.uk/ws/files/195933331/180113983_Prediction_of_emergence_from_prolonged_disorders_of_consciousness.pdf
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Superior Title: Kung , B , Chiang , M , Perera , G , Pritchard , M & Stewart , R 2022 , ' Unsupervised Machine Learning to Identify Depressive Subtypes ' , Healthcare Informatics Research , vol. 28 , no. 3 , pp. 256-266 . https://doi.org/10.4258/hir.2022.28.3.256
Subject Terms: Psychiatry, Depression, Mental Health, Machine Learning, Medical Informatics
File Description: application/pdf
Contributors: Koucheryavy, Yevgeni, Balandin, Sergey, Andreev, Sergey
Superior Title: Tung , S P , Wong , K Y , Kuzminykh , I , Bakhshi , T & Ghita , B 2022 , Using a Machine Learning Model for Malicious URL Type Detection . in Y Koucheryavy , S Balandin & S Andreev (eds) , Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 21st International Conference, NEW2AN 2021, and 14th Conference, ruSMART 2021, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 13158 LNCS , Springer Science and Business Media Deutschland GmbH , ....
Subject Terms: Lexical Feature, Machine Learning, Malicious URL, Malware, Phishing, Spamming, Traffic, Web Security
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Availability:
https://doi.org/10.1007/978-3-030-97777-1_41
https://kclpure.kcl.ac.uk/portal/en/publications/44278b48-e7ff-4570-8452-7efb6401bb52
https://kclpure.kcl.ac.uk/ws/files/254408844/Using_a_Machine_Learning_Model_for_Malicious_URL_Type_Detection.pdf
http://www.scopus.com/inward/record.url?scp=85127880306&partnerID=8YFLogxK
Superior Title: 2022 , ' Machine learning–derived major adverse event prediction of patients undergoing transvenous lead extraction : Using the ESC EHRA EORP European lead extraction ConTRolled ELECTRa registry ' , Heart Rhythm , vol. 19 , no. 6 , pp. 885-893 . https://doi.org/10.1016/j.hrthm.2021.12.036
Subject Terms: Artificial intelligence, ELECTRa registry, Machine learning, Outcomes, Risk stratification, Transvenous lead extraction
Authors: Xie, Feng, Liu, Nan, Yan, Linxuan, Ning, Yilin, Lim, Ka Keat, Gong, Changlin, Kwan, Yu Heng, Ho, Andrew Fu Wah, Low, Lian Leng, Chakraborty, Bibhas, Ong, Marcus Eng Hock
Superior Title: Xie , F , Liu , N , Yan , L , Ning , Y , Lim , K K , Gong , C , Kwan , Y H , Ho , A F W , Low , L L , Chakraborty , B & Ong , M E H 2022 , ' Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions ' , EClinicalMedicine , vol. 45 , 101315 . https://doi.org/10.1016/j.eclinm.2022.101315
Subject Terms: AutoScore, Emergency, Interpretable machine learning, Patient readmission, Scoring system
Superior Title: Campbell , C , Plangger , K , Sands , S , Kietzmann , J H & Bates , K 2022 , ' How Deepfakes and Artificial Intelligence Could Reshape the Advertising Industry ' , JOURNAL OF ADVERTISING RESEARCH , vol. 62 , no. 3 , pp. 241-251 . https://doi.org/10.2501/JAR-2022-017
Subject Terms: Manipulated advertising, creativity, deepfakes, generative adversarial networks (GANs), artificial intelligence (AI), machine learning
File Description: application/pdf
Availability:
https://doi.org/10.2501/JAR-2022-017
https://kclpure.kcl.ac.uk/portal/en/publications/a174a058-7939-49c5-97bf-c9cc35a57a2a
https://kclpure.kcl.ac.uk/ws/files/175092934/Campbell_et_al._2022_The_coming_reality_of_fakes_JAR.pdf
http://www.scopus.com/inward/record.url?scp=85137430982&partnerID=8YFLogxK
Authors: Freire-Aradas, A., Girón-Santamaría, L., Mosquera-Miguel, A., Ambroa-Conde, A., Phillips, C., Casares de Cal, M., Gómez-Tato, A., Álvarez-Dios, J., Pospiech, E., Aliferi, A., Syndercombe Court, D., Branicki, W., Lareu, M. V.
Superior Title: Freire-Aradas , A , Girón-Santamaría , L , Mosquera-Miguel , A , Ambroa-Conde , A , Phillips , C , Casares de Cal , M , Gómez-Tato , A , Álvarez-Dios , J , Pospiech , E , Aliferi , A , Syndercombe Court , D , Branicki , W & Lareu , M V 2022 , ' A common epigenetic clock from childhood to old age ' , Forensic Science International: Genetics , vol. 60 , 102743 . https://doi.org/10.1016/j.fsigen.2022.102743
Subject Terms: DNA methylation, EpiTYPER®, Forensic age estimation, Machine learning, Quantile regression
Authors: Aliferi, Anastasia, Sundaram, Sudha, Ballard, David, Freire-Aradas, Ana, Phillips, Christopher, Lareu, Maria Victoria, Court, Denise Syndercombe
Superior Title: Aliferi , A , Sundaram , S , Ballard , D , Freire-Aradas , A , Phillips , C , Lareu , M V & Court , D S 2022 , ' Combining current knowledge on DNA methylation-based age estimation towards the development of a superior forensic DNA intelligence tool ' , Forensic Science International: Genetics , vol. 57 , 102637 . https://doi.org/10.1016/j.fsigen.2021.102637
Subject Terms: Age prediction, DNA intelligence, DNA methylation, Forensic, Machine learning
File Description: application/pdf
Availability:
https://doi.org/10.1016/j.fsigen.2021.102637
https://kclpure.kcl.ac.uk/portal/en/publications/32b9021f-ab34-42bd-adc7-b64e9e28e24c
https://kclpure.kcl.ac.uk/ws/files/164719668/Combining_current_knowledge_on_ALIFERI_Publishedonline24November2021_GREEN_AAM_CC_BY_NC_ND_.pdf
http://www.scopus.com/inward/record.url?scp=85120058263&partnerID=8YFLogxK
Superior Title: 2022 , ' Ethical considerations for precision psychiatry : A roadmap for research and clinical practice ' , European Neuropsychopharmacology , vol. 63 , pp. 17-34 . https://doi.org/10.1016/j.euroneuro.2022.08.001
Subject Terms: Humans, Machine Learning, Mental Disorders/diagnosis, Psychiatry
Authors: Farajidavar, Nazli, O’Gallagher, Kevin, Bean, Daniel, Nabeebaccus, Adam, Zakeri, Rosita, Bromage, Daniel, Kraljevic, Zeljko, Teo, James T.H., Dobson, Richard J., Shah, Ajay M.
Superior Title: Farajidavar , N , O’Gallagher , K , Bean , D , Nabeebaccus , A , Zakeri , R , Bromage , D , Kraljevic , Z , Teo , J T H , Dobson , R J & Shah , A M 2022 , ' Diagnostic signature for heart failure with preserved ejection fraction (HFpEF) : a machine learning approach using multi-modality electronic health record data ' , BMC Cardiovascular Disorders , vol. 22 , no. 1 , 567 . https://doi.org/10.1186/s12872-022-03005-w
Subject Terms: Dyspnea, HFpEF, Machine learning
Superior Title: Nicholls , J K , Ince , J , Minhas , J S & Chung , E M L 2022 , ' Emerging Detection Techniques for Large Vessel Occlusion Stroke: A Scoping Review ' , Frontiers in Neurology , vol. 12 , 780324 . https://doi.org/10.3389/fneur.2021.780324
Subject Terms: Neurology, large vessel occlusion, LVO, stroke, stroke scale, biomarkers, algorithms, machine learning, imaging
File Description: application/pdf
Authors: Brusini, Irene, MacNicol, Eilidh, Kim, Eugene, Smedby, Örjan, Wang, Chunliang, Westman, Eric, Veronese, Mattia, Turkheimer, Federico, Cash, Diana
Superior Title: Brusini , I , MacNicol , E , Kim , E , Smedby , Ö , Wang , C , Westman , E , Veronese , M , Turkheimer , F & Cash , D 2022 , ' MRI-derived brain age as a biomarker of ageing in rats : validation using a healthy lifestyle intervention ' , Neurobiology of Aging , vol. 109 , pp. 204-215 . https://doi.org/10.1016/j.neurobiolaging.2021.10.004
Subject Terms: Biomarker, Brain ageing, BrainAGE, Machine learning, Neuroimaging, Rat models