Classification method based on surf and sift features for alzheimer diagnosis using diffusion tensor magnetic resonance imaging by Nourhan Zayed, Ghaidaa Eldeep, Inas A. Yassine

“…Using FA features for binary discrimination achieves 97.5%. …”
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Nemaline myopathy: clinical, histochemical and immunohistochemical features Miopatia nemalínica: achados clínicos, histoquímicos e imuno-histoquímicos by Nazah Cherif Mohamad Youssef, Rosana Herminia Scola, Paulo José Lorenzoni, Lineu César Werneck

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Clinical and Psychopathological Features of Mental Disorders in Patients with Poisoning by Hypotensive and Antiarrhythmic Drugs as a Result of Suicidal Acts by T. I. Dikaya, K. K. Ilyashenko, G. N. Sukhodolova, O. V. Zubareva, M. M. Potskhveriya

“…To study the clinical and psychopathological features of mental disorders in patients with acute poisoning by hypotensive and antiarrhythmic drugs as a result of suicidal acts.   …”
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IDENTIFICATION OF FIREARMS BY TOOLMARKS ON FIRED BULLETS AND SPENT CARTRIDGE CASES EXPOSED TO THERMAL IMPACT AFTER THE FIREARM DISCHARGE by I. Latyshov, M. Pakhomov

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Features of the expression of genes of antimicrobial peptides and the microbiome at the level of the mucous membrane of the upper respiratory tract during aging by V. V. Burmakina, N. O. Vartanova, M. V. Khoreva, S. V. Gorodishchenskaya, A. S. Avagyan, O. A. Svitich

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Inheritance features of productivity traits in pea hybrids F₁ and F₂ by F. A. Davletov, K. P. Gainullina, А. М. Dmitriev, E. V. Badamshina

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Biomass prediction of Typha latifolia on a paludiculture site by combining structural and spectral features from UAS data by Christina Hellmann, Bernd Bobertz, Fabian Hübner, Nora Köhn, Jürgen Kreyling, Sebastian van der Linden

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Integration of UAV-sensed features using machine learning methods to assess species richness in wet grassland ecosystems by Clara Oliva Gonçalves Bazzo, Bahareh Kamali, Murilo dos Santos Vianna, Dominik Behrend, Hubert Hueging, Inga Schleip, Paul Mosebach, Almut Haub, Axel Behrendt, Thomas Gaiser

“…RF models generally outperformed PLS models across different feature sets, with the CH + VI + GLCM combination yielding the best results. …”
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The association between tumor-stromal collagen features and the clinical outcomes of patients with breast cancer: a systematic review by Samane Heydari, Fatemeh Tajik, Sadegh Safaei, Fereshteh Kamani, Babak Karami, Shima Dorafshan, Zahra Madjd, Roya Ghods

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A flow pattern recognition method for gas-liquid two-phase flow based on dilated convolutional channel attention mechanism. by Jie Liu, Yang Wu

“…Addressing the issue of insufficient key feature extraction leading to low recognition rates in existing deep learning-based flow pattern identification methods, this paper proposes a novel flow pattern image recognition model, Enhanced DenseNet with transfer learning (ED-DenseNet). …”
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Transcriptional features of autoimmune diabetes: differentially expressed genes in CD4+ and CD8+ subpopulations of blood T cells by I. I. Golodnikov, E. S. Podshivalova, V. I. Chechekhin, A. V. Zubritsky, A. A. Matrosova, Y. V. Dvoryanchikov, M. D. Samsonova, E. K. Markelova, Y. A. Medvedeva, T. V. Nikonova, E. V. Bondarenko, S. V. Popov, I. R. Minniakhmetov, M. V. Shestakova

“…When comparing LADA to T1DM, only one transcript, C20orf204, showed statistically significant differential expression (p<0.05) in CD4+ Naive T-cells.CONCLUSION: The findings indicate that LADA and T1DM share similar molecular patterns, with LADA exhibiting moderate changes in the expression of genes associated with immune regulation and inflammation. …”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…This transformation improves feature extraction by capturing more discriminative patterns, leading to superior performance compared to conventional methods. …”
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Association between ultrasound-based biliary and parenchymal intrahepatic mass-forming cholangiocarcinoma subtypes and clinicopathological features and survival by Cong-Jian Wen, Hui Liu, Li-Ping Sun, Chong-Ke Zhao, Hao-Hao Yin, Li-Fan Wang, Ming-Rui Zhu, Yi-Kang Sun, Ya-Qin Zhang, Zi-Tong Chen, Xi Wang, Han-Sheng Xia, Hong Han, Hui-Xiong Xu, Bo-Yang Zhou

“…We aimed to subclassify MF-ICC into biliary and parenchymal types based on ultrasound (US) findings and to investigate the differences in their contrast-enhanced ultrasound (CEUS) patterns, clinicopathologic features, and prognosis. …”
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Computed Tomography Scan and Clinical-based Complete Response Prediction in Locally Advanced Rectal Cancer after Neoadjuvant Chemoradiotherapy: A Machine Learning Approach by Seyyed Hossein Mousavie Anijdan, Daryush Moslemi, Reza Reiazi, Hamid Fallah Tafti, Ali Akbar Moghadamnia, Reza Paydar

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Simultaneous Instance and Attribute Selection for Noise Filtering by Yenny Villuendas-Rey, Claudia C. Tusell-Rey, Oscar Camacho-Nieto

“…Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. …”
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Advancing skin cancer detection integrating a novel unsupervised classification and enhanced imaging techniques by Md. Abdur Rahman, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Mirjam Jonkman, Friso DeBoer, Sami Azam

“…The authors aim to bridge the gap in dermatological research by introducing innovative techniques that enhance image quality and improve feature extraction. To achieve this, enhanced super‐resolution generative adversarial networks (ESRGAN) was fine‐tuned to strengthen the resolution of skin lesion images, making critical features more visible. …”
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Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures by Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim

“…The empirical results ratify that the pre-trained network learns better (accuracy up to 0.91); that using acoustic features can improve the results marginally (up to 13 percentage points of difference) depending on the time-frequency input and main architecture; and that combining spectrogram representations with acoustic features yields the best results (accuracy up to 0.91).…”
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A Deep Learning Approach to Unveil Types of Mental Illness by Analyzing Social Media Posts by Rajashree Dash, Spandan Udgata, Rupesh K. Mohapatra, Vishanka Dash, Ashrita Das

“…After examining the linguistic patterns of different social media posts, a reduced feature space is generated using appropriate feature engineering, which is further fed as input to the LSTM model to identify a type of mental illness. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…This cross-sectional study aimed to identify and cluster gait patterns using an end-to-end deep learning approach that autonomously extracts features from joint angle trajectories for a gait cycle, minimizing human intervention. …”
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Modified Gray-Level Haralick Texture Features for Early Detection of Diabetes Mellitus and High Cholesterol with Iris Image by Rinci Kembang Hapsari, Miswanto Miswanto, Riries Rulaningtyas, Herry Suprajitno, Gan Hong Seng

“…Traces related to the intensity or deviation of organs caused by the disease are recorded systematically and patterned on the iris and its surroundings. The pattern that appears on the iris can be recognized by using image processing techniques. …”
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