Multimodal convolutional transformer (mct-dd): depression diagnosis through joint task analysis; Молодежь и современные информационные технологии

Multimodal convolutional transformer (mct-dd): depression diagnosis through joint task analysis; Молодежь и современные информационные технологии

Bibliografske podrobnosti
Parent link:	Молодежь и современные информационные технологии.— 2024.— С. 47-51
Glavni avtor:	Firoz N.
Drugi avtorji:	Berestneva O. G. Olga Grigorievna, Aksenov S. V. Sergey Vladimirovich
Izvleček:	A new deep learning method, Multimodal Convolutional Transformer, analyzes EEG and genetic data to diagnose MDD. This approach achieved high accuracy (97.16%) and surpasses other methods for early MDD detection, potentially aiding healthcare professionals Текстовый файл
Jezik:	angleščina
Izdano:	2024
Serija:	Искусственный интеллект, машинное обучение и большие данные
Teme:	электронный ресурс труды учёных ТПУ genetics transformers EEG Deep Learning
Online dostop:	http://earchive.tpu.ru/handle/11683/84880
Format:	Elektronski Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=675176

Podobne knjige/članki

Research on neural network analysis of MRI images of the brain for the diagnosis of brain diseases; Молодежь и современные информационные технологии
od: Tekere R. Richard
Izdano: (2025)

Study of nanosecond pulse switches for low voltage generator for diagnosis of power transformers; Mechanical Engineering, Automation and Control Systems (MEACS)
Izdano: (2014)

Classification of audio samples by convolutional networks in audiobeehive monitoring; Вестник Томского государственного университета. Управление, вычислительная техника и информатика; № 45
od: Кулюкин В. А. Владимир Алексеевич
Izdano: (2018)

Molecular Diagnosis of Genetic Diseases
Izdano: (2004)

Prenatal Diagnosis
Izdano: (2008)

Atlas of Genetic Diagnosis and Counseling
od: Chen, Harold
Izdano: (2017)

Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network; Control and Communications (SIBCON-2017)
Izdano: (2017)

Оценка использования инструментов библиотеки SpaCy и DeepPavlov для задачи извлечения именованных сущностей из описаний результатов осмотров пациентов с COVID-19; Известия Томского политехнического университета [Известия ТПУ]. Промышленная кибернетика; Т. 1, № 2
Izdano: (2023)

Aortography Keypoint Tracking for Transcatheter Aortic Valve Implantation Based on Multi-Task Learning; Frontiers in Cardiovascular Medicine; Vol. 8
Izdano: (2021)

Методы инспекции пакетов и анализа трафика. Технология Deep Packet Inspection учебно-методическое пособие
od: Гольдштейн Б. С.
Izdano: (Санкт-Петербург, СПбГУТ им. М.А. Бонч-Бруевича, 2018)

Детектирование уровней поддержки и сопротивления с использованием блока автоматической генерации признаков; Молодежь и современные информационные технологии
od: Хайров М. А.
Izdano: (2024)

Использование инструментов MedSpaCy и DeepPavlov для извлечения симптомов COVID-19 и лекарств из медицинских текстов; Молодежь и современные информационные технологии
od: Соколовский Д. Е.
Izdano: (2024)

A novel facile approach to obtain phenytoin and thiophenytoin using new deep eutectic solvent-like mixtures of urea, thiourea, and KOH; Chemistry of Heterocyclic Compounds; Vol. 60, iss. 1-2
Izdano: (2024)

Prediction performance advantages of deep machine learning algorithms for two-phase flow rates through wellhead chokes; Journal of Petroleum Exploration and Production; Vol. ХХ, iss. XX
Izdano: (2021)

A Discreet Mathematical Model Based on the Bilinear Transformation of a Synchronous Electric Machine with a Turn-to-Turn Fault in the Rotor Winding; Russian Electrical Engineering; Vol. 90, iss. 2
Izdano: (2019)

Predicting oil flow rate through orifice plate with robust machine learning algorithms; Flow Measurement and Instrumentation; Vol. 81
Izdano: (2021)

Luminescent glasses for transformation of X-ray emission in radiation introscopes; Bulletin of the Tomsk Polytechnic University; Vol. 310, № 1
Izdano: (2007)

The Matlab Simulink model of transformer winding when its diagnisis by short duration puls takes place; Mechanical Engineering, Automation and Control Systems (MEACS)
Izdano: (2014)

Application of several time-frequency analysis methods to the spectral analysis of rock fracture signals; Перспективы развития фундаментальных наук; Т. 1 : Физика
od: Luo J.
Izdano: (2024)

Акустические исследования глубоководных газовых факелов Охотского моря; Известия Томского политехнического университета [Известия ТПУ]. Инжиниринг георесурсов; Т. 332, № 10
Izdano: (2021)

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution; Computing and Software for Big Science; Vol. 2020, iss. 4
Izdano: (2020)

Синтез гидрофильных глубоких эвтектических растворителей на основе принципов зелёной химии для повышения нефтеотдачи в Арктических регионах; Перспективы развития фундаментальных наук; Т. 2 : Химия
od: Шолидодов М. Р.
Izdano: (2025)

Повышение безопасности при эксплуатации трансформаторных подстанций; Ресурсосберегающие технологии в контроле, управлении качеством и безопасности
od: Люкию Е. С. Елена Сергеевна
Izdano: (2021)

Development and research of mathematical model of current transformer reproducing magnetic hysteresis based on Preisach theory; IET Generation, Transmission & Distribution; Vol. 14, iss. 14
Izdano: (2020)

Глубокие искусственные нейронные сети для прогноза значений дебитов добывающих скважин; Известия Томского политехнического университета [Известия ТПУ]. Инжиниринг георесурсов; Т. 331, № 11
od: Евсюткин И. В. Иван Викторович
Izdano: (2020)

Comparative Study of Deep Learning Modelsfor Automatic Coronary Stenosis Detectionin X-ray Angiography; CEUR Workshop Proceedings; Vol. 2744 : GraphiCon 2020. Computer Graphics and Machine Vision
Izdano: (2020)

Progress in low energy high intensity ion implantation method development; Surface and Coatings Technology; Vol. 388
od: Ryabchikov A. I. Aleksandr Ilyich
Izdano: (2020)

Cancer Epigenetics Risk Assessment, Diagnosis, Treatment, and Prognosis /
Izdano: (2015)

Advances in Reinforcement Learning: A Comprehensive Review of Real-World Applications in Industry; Acta Scientific Computer Sciences; Vol. 5, iss. 5
od: Usenko K. Kirill
Izdano: (2023)

Constraints on the appearance of a maximum in astrophysical S-factor; Physics Letters B; Vol. 824
Izdano: (2022)

Methods of Forecasting Electric Energy Consumption: A Literature Review; Energies; Vol. 15, iss. 23
Izdano: (2022)

Probing transversity by measuring Λ polarisation in SIDIS; Physics Letters B; Vol. 824
Izdano: (2022)

On the issue of historiography of the study of the phenomenon of smarttechnologies that affect the transformation of society in modernconditions; Journal of Economics and Social Sciences; № 15
od: Netesova M. V. Mariya Vitalevna
Izdano: (2019)

Calculation of the Parameters of a Two-Winding Transformer without a Magnetic Circuit; Russian Electrical Engineering; Vol. 91, iss. 6
od: Nosov G. V. Gennady Vasilievich
Izdano: (2020)

Bacterial inhibition and biofilm eradication ability of low-toxic deep eutectic solvents prepared from lactic acid and quaternary ammonium compounds; Materials Letters; Vol. 378
Izdano: (2025)

Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids; Journal of Industrial Information Integration; Vol. 41
Izdano: (2024)

Settings determination for numerical transformer differential protection via its detailed mathematical model; IET Generation, Transmission & Distribution; Vol. 14, iss. 10
Izdano: (2020)

Development of a Neural Network for a Digital Twin of Three-Winding Transformer; Problems of Informatics, Electronics and Radio Engineering (PIERE)
Izdano: (2024)

Lithogenesis of vend-cambrian deposits of southwest slope of Baikitskaya anteclase (based on the study of the section of the Irinchiminskaya parametrical well 155 in East Siberia); Bulletin of the Tomsk Polytechnic University; Vol. 311, № 1
Izdano: (2007)

Antiproton over proton and K- over K+ multiplicity ratios at high z in DIS; Physics Letters B; Vol. 807
Izdano: (2020)