A machine learning approach to aerosol classification for single-particle mass spectrometry by Christopoulos, Costa (Costa D.), Garimella, Sarvesh, Zawadowicz, Maria Anna, Cziczo, Daniel James

“…In this study, classifiers are created using a data set of SPMS spectra to automatically differentiate particles on the basis of chemistry and size. …”
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Differentiation of Benign and Malignant Breast Lesions Based on Multimodal MRI and Deep Learning by YANG Yi-feng, QI Zhang-xuan, NIE Sheng-dong

“…The experimental results show that the proposed algorithm performs well in the classification of benign and malignant breast lesions with small sample size, and the fusion model based on multimodal data further enriches the feature information, thus this study improves the detection accuracy of lesions, and provides a new method for automatic differential diagnosis of benign and malignant breast lesions.…”
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Estimation of SPIO Nanoparticles Uptakes by Macrophages Using Transmission Electron Microscopy by Adham Aleid, Khalid Alhussaini, Mohammed Almijalli, Ali S. Saad

“…The Otsu threshold method is a global thresholding technique used to automatically differentiate SPIOs from the background. The SPIO-NPs appear in red colors, and the other pixels in the image are considered background. …”
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Use of artificial intelligence for the diagnosis of cholesteatoma by Christopher C. Tseng, Valerie Lim, Robert W. Jyung

“…An image classification workflow was developed to automatically differentiate cholesteatomas from other possible tympanic membrane appearances. …”
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Echocardiography-based machine learning algorithm for distinguishing ischemic cardiomyopathy from dilated cardiomyopathy by Mei Zhou, Yongjian Deng, Yi Liu, Xiaolin Su, Xiaocong Zeng

“…The present study examined the diagnostic value of a ML algorithm that combines echocardiographic data to automatically differentiate ischemic cardiomyopathy (ICM) from dilated cardiomyopathy (DCM). …”
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Player motion analysis : automatically classifying NBA plays by Kates, Mitchell (Mitchell H.)

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A machine-learning approach to aerosol classification for single-particle mass spectrometry by Christopoulos, Costa (Costa D.)

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Raman-based spectrophenotyping of the most important cells of the immune system by Aleksandra Borek-Dorosz, Anna Maria Nowakowska, Patrycja Leszczenko, Adriana Adamczyk, Anna Pieczara, Justyna Jakubowska, Agata Pastorczak, Kinga Ostrowska, Marta Ząbczyńska, Karol Sowinski, Wieslaw Ignacy Gruszecki, Malgorzata Baranska, Katarzyna Maria Marzec, Katarzyna Majzner

“…Conclusions: This proves the potential of Raman spectroscopy in clinical diagnostics to automatically differentiate between cells that are an important component of our immune system.…”
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Better-Weeds – Next generation weed management by Redwitz, Christoph von, Kämpfer, Christoph, Hodac, Ladislav, Mäder, Patrick, Pflanz, Michael, Milz, Stefan, Rüdiger, Tobias, Schatke, Mona, Ulber, Lena, Wäldchen, Jana

“…Sensor-based recognition systems automatically differentiate between weed and crop plants allowing for selective and site-specific weed control measures. …”
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Automated Diagnosis of Prostate Cancer Using mpMRI Images: A Deep Learning Approach for Clinical Decision Support by Anil B. Gavade, Rajendra Nerli, Neel Kanwal, Priyanka A. Gavade, Shridhar Sunilkumar Pol, Syed Tahir Hussain Rizvi

“…Deep learning (DL) approaches can be beneficial in this regard by automatically differentiating relevant features and providing an automated diagnosis of PCa. …”
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Can large language models write reflectively by Yuheng Li, Lele Sha, Lixiang Yan, Jionghao Lin, Mladen Raković, Kirsten Galbraith, Kayley Lyons, Dragan Gašević, Guanliang Chen

“…Furthermore, we explored the extent to which Deep Learning classification methods can be utilised to automatically differentiate between reflective responses written by students vs. reflective responses generated by ChatGPT. …”
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Efficient and scalable methods for deep reinforcement learning by Farquhar, G

“…In Chapter 8 we propose an objective which may be (automatically) differentiated any number of times to produce unbiased estimates of higher-order derivatives. …”

Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections by Arjun Sarkar, Jan-Philipp Praetorius, Marc Thilo Figge

“…The applied CNN demonstrates the potential for automatically differentiating bloodstream Candida infections with high accuracy and efficiency. …”
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Binary semantic segmentation for detection of prostate adenocarcinoma using an ensemble with attention and residual U-Net architectures by Kasikrit Damkliang, Paramee Thongsuksai, Kanita Kayasut, Thakerng Wongsirichot, Chanwit Jitsuwan, Tarathep Boonpipat

“…Deep learning has been used to automatically differentiate GP on digitized slides, aiding pathologists and reducing inter-observer variability, especially in the early GP of cancer. …”
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Features and methods for improving large scale face recognition by Parkhi, O

“…We also propose a scheme to automatically differentiate the primary cast of a TV serial or movie from that of the background characters. …”

Differential diagnosis of frontotemporal dementia subtypes with explainable deep learning on structural MRI by Da Ma, Jane Stocks, Howard Rosen, Kejal Kantarci, Samuel N. Lockhart, James R. Bateman, Suzanne Craft, Metin N. Gurcan, Karteek Popuri, Mirza Faisal Beg, Lei Wang, Lei Wang, on behalf of the ALLFTD consortium

“…In the present study, we aim to automatically differentiate patients with three clinical phenotypes of FTD, behavioral-variant FTD (bvFTD), semantic variant PPA (svPPA), and nonfluent variant PPA (nfvPPA), based on their structural MRI by training a deep neural network (DNN).MethodsData from 277 FTD patients (173 bvFTD, 63 nfvPPA, and 41 svPPA) recruited from two multi-site neuroimaging datasets: the Frontotemporal Lobar Degeneration Neuroimaging Initiative and the ARTFL-LEFFTDS Longitudinal Frontotemporal Lobar Degeneration databases. …”
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Dynamical Reduced-Order Models for High-Dimensional Systems by Charous, Aaron

“…Lastly, with tools from machine learning, we introduce learnable and automatically differentiable coordinate transforms. The compressibility of a system heavily depends on the choice of coordinates, and frequently a coordinate system is chosen for its simplicity rather than its efficiency. …”
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