Dominant twin peaks: a novel conjecture for the pathophysiologic basis of tremor frequency and fluctuation time in Parkinson’s disease by Furrukh Khan, David Novikov, Brian Dalm, Jessie Xiaoxi, Oliver Flouty, Evan Thomas

“…Correlating subthalamic synchronized oscillatory activity with motor impairment in Parkinson’s disease patients has recently gained attention in the literature.ObjectiveBased on the deep brain recordings of a Parkinson’s disease patient our objective is to (i) Use actual measurements of the patient’s tremor to support a hypothesis that connects the features of the Local Field Potential’s beta-band spectrum (13–31 Hz), with the lower frequency (4–8 Hz) features of the patient’s tremor, such as tremor frequency and tremor fluctuation time and (ii) Justify the hypothesis through theoretical reasoning based on communication theory in Electrical Engineering.MethodsTremor characteristics (i.e., tremor frequency and tremor fluctuation time) derived from limb coordinate time-series were obtained from a video of the patient by using Google’s MediaPipe Artificial Intelligence Framework. …”
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New Horizons In The Treatment Of Metastatic Castrate Resistant Prostate Cancer by Zein El Amir

“…-trained anatomists are now an almost extinct species in the country adding to the multitude of challenges already faced in anatomy teaching.   …”
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Anatomy In The Undergraduate Medical Curriculum; Blending The Old And New by Ayesha Yousaf

“…Anatomists now form a very small community, and their training level has deteriorated.[x] Pakistan has not been spared by this pedagogical plague and PHd trained anatomists are now an almost extinct species in the country adding to the multitude of challenges already faced in anatomy teaching. …”
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EDITORIAL by Ivan Čuk

“…Our journal has been recently entered into the ErihPlus data base for humanities and social sciences. The process of evaluation took more than half a year but was successfully completed. …”
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Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus by Xiuli Feng, Renhao Zhao, Teng Yang, Na Wang, Guofeng Wang

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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…Principal component analysis is also utilized (PCA) to extract features, hence expediting the entire process by reducing dimensionality. …”
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CloudSense: A model for cloud type identification using machine learning from radar data by Mehzooz Nizar, Jha K. Ambuj, Manmeet Singh, S.B. Vaisakh, G. Pandithurai

“…The machine learning (ML) model used in CloudSense was trained using a dataset balanced by Synthetic Minority Oversampling Technique (SMOTE), with features selected based on physical characteristics relevant to different cloud types. …”
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Early and accurate nutrient deficiency detection in hydroponic crops using ensemble machine learning and hyperspectral imaging by Nagarajan S․, Maria Merin Antony, Murukeshan Vadakke Matham

“…In the proposed approach, the features extracted from hyperspectral datacubes are trained to create machine learning models. …”
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Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

“…We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. …”
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Arabic Temporal Common Sense Understanding by Reem Alqifari, Hend Al-Khalifa, Simon O’Keefe

“…Based on this, the effectiveness of these models in Arabic and English is compared and discussed. …”
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Enhancing fairness in disease prediction by optimizing multiple domain adversarial networks. by Bin Li, Xiaoqian Jiang, Kai Zhang, Arif O Harmanci, Bradley Malin, Hongchang Gao, Xinghua Shi, Alzheimer’s Disease Neuroimaging Initiative

“…However, current approaches struggle to simultaneously mitigate biases induced by multiple sensitive features in biomedical data. To enhance fairness, we introduce a framework based on a Multiple Domain Adversarial Neural Network (MDANN), which incorporates multiple adversarial components. …”
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Deep neural networks and fractional grey lag Goose optimization for music genre identification by Yuanye Tian

“…The model consists of two main parts: a pre-trained model, a ZFNet, through which high level features are extracted from audio signals and a ResNeXt model for classification. …”
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Mapping dominant plant communities in the degraded Zoige swamp using Sentinel-1/2 imagery and its implications for vegetation restoration by Guoying Zhang, Chuanpeng Zhao, Mingming Jia, Rong Zhang, Hou Jiang, Zongming Wang

“…Finally, we reconstructed the decision rules based on the trained RF model. The results showed that Carex could be identified through the image characteristics of the fruiting season, whereas the other two communities required dual-phase image features, wherein the identification of Kobresia was particularly challenging. …”
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Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

“…These pre-trained models are more effective for general image classification and struggle with the nuanced features and class imbalances inherent in medical image datasets. …”
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ON DESIGN OF PREDICTIVE MODEL FOR HEART DISEASE by Soumyendu Bhattacharjee, Susmita Das, Sangita Roy, Arpita Santra, Anasuya Sarkar, Moumita Pa, Biswarup Neogi

“…Three algorithms are used to train these medical features: Random Forest Classifier, KNN, and Logistic Regression.…”
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Remote Monitoring of Chemotherapy-Induced Peripheral Neuropathy by the NeuroDetect iOS App: Observational Cohort Study of Patients With Cancer by Ciao-Sin Chen, Michael P Dorsch, Sarah Alsomairy, Jennifer J Griggs, Reshma Jagsi, Michael Sabel, Amro Stino, Brian Callaghan, Daniel L Hertz

“…Various classification models including NeuroDetect features only (NeuroDetect Model) CIPN20-only (CIPN20 Model) or a combination of both (Combined Model) were trained and evaluated for accuracy in predicting CIPN probability. …”
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Customizable pattern synthesis: a deep generative approach for lantern designs by Mengran Yan, Chun Tang, Jida Yan, Siti Suhaily Surip

“…Our research presents an innovative generative model that produces customizable lantern patterns, integrating classical aesthetics with modern design features via a generative adversarial network (GAN)-based framework. …”
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GPU Accelerated Trilateral Filter for MR Image Restoration by Suthir Sriram, Nivethitha Vijayaraj, T. Srilekha, M. Praveena, Thangavel Murugan

“…The approach uses forward selection to identify 98 texture attributes while refining the selection process to find optimal regularity features. A two-phase classification system trains automation parameters using artificial neural networks together with support vector machines. …”
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Biological heart and brain ageing in subjects with cardiovascular diseases by Elizabeth Mcavoy, Elizabeth Mcavoy, Elizabeth Mcavoy, Matthias Wilms, Matthias Wilms, Matthias Wilms, Matthias Wilms, Matthias Wilms, Nils D. Forkert, Nils D. Forkert, Nils D. Forkert, Nils D. Forkert

“…For BAG computation, a convolutional neural network was trained based on the MRI data, while a CatBoost model was trained for HAG analyses based on the tabulated cardiac features. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Five non-invasive features—BRI, waist circumference, height, age, and gender—were used as predictors. …”
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