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Machine Learning Models Identify Multimodal Measurements Highly Predictive of Transdiagnostic Symptom Severity for Mood, Anhedonia, and Anxiety
Mellem, Monika S., Liu, Yuelu, Gonzalez, Humberto, Kollada, Matthew, Martin, William J., Ahammad, Parvez
Published in Biological psychiatry : cognitive neuroscience and neuroimaging (01.01.2020)
Published in Biological psychiatry : cognitive neuroscience and neuroimaging (01.01.2020)
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On the Privacy Risks of Deploying Recurrent Neural Networks in Machine Learning Models
Yang, Yunhao, Gohari, Parham, Topcu, Ufuk
Published in Proceedings on Privacy Enhancing Technologies (01.01.2023)
Published in Proceedings on Privacy Enhancing Technologies (01.01.2023)
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Predicting Autonomic Dysfunction in Anxiety Disorder from ECG and Respiratory Signals Using Machine Learning Models
George, Abhilash Saj, Kurup, Arjun Vijayanatha, Balachandran, Parthasarathy, Nair, Manjusha, Gopinath, Siby, Kumar, Anand, Parasuram, Harilal
Published in International Journal of Online and Biomedical Engineering (01.01.2021)
Published in International Journal of Online and Biomedical Engineering (01.01.2021)
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Automated Training and Deployment of Machine-Learning Models for Anomaly Detection in Telemetry
Naik, Kedar, Palmer, Andrew, Kenworthy, John
Published in 2022 IEEE Aerospace Conference (AERO) (05.03.2022)
Published in 2022 IEEE Aerospace Conference (AERO) (05.03.2022)
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The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?Research in context
Joan Martínez Vidal, Nikos Tsiknakis, Johan Staaf, Ana Bosch, Anna Ehinger, Emma Nimeus, Roberto Salgado, Yalai Bai, David L. Rimm, Johan Hartman, Balazs Acs
Published in EClinicalMedicine (01.12.2024)
Published in EClinicalMedicine (01.12.2024)
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Comparison of Machine Learning Models to Predict Risk of Falling in Osteoporosis Elderly
Cuaya-Simbro, German, Perez-Sanpablo, Alberto-Isaac, Muñoz-Meléndez, Angélica, Uriostegui, Ivett Quiñones, Morales-Manzanares, Eduardo-F., Nuñez-Carrera, Lidia
Published in Foundations of computing and decision sciences (01.06.2020)
Published in Foundations of computing and decision sciences (01.06.2020)
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Can Sequential Images from the Same Object Be Used for Training Machine Learning Models? A Case Study for Detecting Liver Disease by Ultrasound Radiomics
Sultan, Laith R., Cary, Theodore W., Al-Hasani, Maryam, Karmacharya, Mrigendra B., Venkatesh, Santosh S., Assenmacher, Charles-Antoine, Radaelli, Enrico, Sehgal, Chandra M.
Published in AI (Basel) (01.09.2022)
Published in AI (Basel) (01.09.2022)
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Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2
Favarato, Martina, Beretta, Andrea, Molteni, Alberto, Fumagalli, Roberto, Perno, Carlo Federico, Bragagnolo, Sara, Grossi, Enzo, Langer, Thomas, Bassi, Gabriele, Zeduri, Anna, Moreno, Mauro, Vismara, Chiara, Gay, Hedwige, Buscema, Massimo, Giudici, Riccardo, Corradin, Matteo, Garberi, Roberta, Villa, Fabiana
Published in Scandinavian journal of trauma, resuscitation and emergency medicine (01.12.2020)
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Published in Scandinavian journal of trauma, resuscitation and emergency medicine (01.12.2020)
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821 Machine learning models can quantify CD8 positivity in lymphocytes in melanoma clinical trial samples
Glass, Benjamin, Adam Stanford-Moore, S, Meghwal, Diksha, Agrawal, Nishant, Lin, Mary, Hedvat, Cyrus, Lee, George, Ely, Scott, Montalto, Michael, Wapinski, Ilan, Baxi, Vipul, Beck, Andrew
Published in Journal for immunotherapy of cancer (01.11.2021)
Published in Journal for immunotherapy of cancer (01.11.2021)
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Comparison of conventional scoring systems to machine learning models for the prediction of major adverse cardiovascular events in patients undergoing coronary computed tomography angiography
Ghorashi, Seyyed Mojtaba, Fazeli, Amir, Hedayat, Behnam, Mokhtari, Hamid, Jalali, Arash, Ahmadi, Pooria, Chalian, Hamid, Bragazzi, Nicola Luigi, Shirani, Shapour, Omidi, Negar
Published in Frontiers in cardiovascular medicine (26.10.2022)
Published in Frontiers in cardiovascular medicine (26.10.2022)
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Supervised Machine Learning Models and Protein-Protein InteractionNetwork Analysis of Gene Expression Profiles Induced by Omega-3 PolyunsaturatedFatty Acids
Sergey Shityakov, Jane Pei-Chen Chang, Ching-Fang Sun, David Ta-Wei Guu, Thomas Dandekar, Kuan-Pin Su
Published in Current Chinese Science (2022)
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Published in Current Chinese Science (2022)
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Machine Learning Models for the Classification of Sleep Deprivation Induced Performance Impairment During a Psychomotor Vigilance Task Using Indices of Eye and Face Tracking
Daley, Matthew S., Gever, David, Posada-Quintero, Hugo F., Kong, Youngsun, Chon, Ki, Bolkhovsky, Jeffrey B.
Published in Frontiers in artificial intelligence (07.04.2020)
Published in Frontiers in artificial intelligence (07.04.2020)
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OTHR-15. Assessment of TRIPOD adherence in articles developing machine learning models for differentiation of glioma from brain metastasis
Jekel, Leon, Brim, Waverly Rose, Petersen, Gabriel Cassinelli, Subramanian, Harry, Zeevi, Tal, Payabvash, Seyedmehdi, Bousabarah, Khaled, Lin, MingDe, Cui, Jin, Brackett, Alexandria, Johnson, Michele, Malhotra, Ajay, Aboian, Mariam
Published in Neuro-oncology advances (09.08.2021)
Published in Neuro-oncology advances (09.08.2021)
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