Bayesian Inference of Hidden Cognitive Performance and Arousal States in Presence of Music by Saman Khazaei, Md Rafiul Amin, Maryam Tahir, Rose T. Faghih

“…<italic>Goal:</italic> Poor arousal management may lead to reduced cognitive performance. …”
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On the Evaluation of the Hyperthermic Efficiency of Magnetic Scaffolds by Matteo B. Lodi, Antonios Makridis, Konstantina Kazeli, Theodoros Samaras, Makis Angelakeris, Giuseppe Mazzarella, Alessandro Fanti

“…<italic>Goal:</italic> Deep-seated tumors (DST) can be treated using thermoseeds exposed to a radiofrequency magnetic field for performing local interstitial hyperthermia treatment (HT). …”
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Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis by Jyun-Yao Jhang, Yu-Ching Tsai, Tzu-Chun Hsu, Chun-Rong Huang, Hsiu-Chi Cheng, Bor-Shyang Sheu

“…<italic>Goal:</italic> Diagnosing the corpus-predominant gastritis index (CGI) which is an early precancerous lesion in the stomach has been shown its effectiveness in identifying high gastric cancer risk patients for preventive healthcare. …”
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Classification of Aortic Stenosis Patients via ECG-Independent Multi-Site Measurements of Cardiac-Induced Accelerations and Angular Velocities at the Skin Level by Chiara Romano, Emanuele Maiorana, Annunziata Nusca, Simone Circhetta, Sergio Silvestri, Schena Emiliano, Gian Paolo Ussia, Carlo Massaroni

“…<italic>Goal:</italic> To evaluate the suitability of seismocardiogram (SCG) and gyrocardiogram (GCG) recorded at the skin level to classify aortic stenosis (AS) patients from healthy volunteers, and to determine the optimal sensor position for the classification. …”
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UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification by Zeyu Ren, Xiangyu Kong, Yudong Zhang, Shuihua Wang

“…<italic>Goal:</italic> Deep learning techniques have made significant progress in medical image analysis. …”
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Low-Rank Adaptation of Pre-Trained Large Vision Models for Improved Lung Nodule Malignancy Classification by Benjamin P. Veasey, Amir A. Amini

“…<italic>Goal:</italic> This paper investigates using Low-Rank Adaptation (LoRA) to adapt large vision models (LVMs) pretrained with self-supervised learning (SSL) for lung nodule malignancy classification. …”
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Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications by Sicong Huang, Roozbeh Jafari, Bobak J. Mortazavi

“…<italic>Results:</italic> a dataset preprocessed by Pulse2AI improved systolic blood pressure estimation by 29.58&#x0025;, from 11.41 to 8.03 mmHg in root-mean-square-error (RMSE) and its diastolic counterpart by 26.01&#x0025;, from 7.93 to 5.87 mmHg in RMSE. …”
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Performance of a Continuous Subcutaneous Insulin Infusion (CSII) Pump With Acoustic Volume and Flow Sensing in Simulated High-Consequence Situations by Robert D. Butterfield, Nathaniel M. Sims

“…<italic>Goal:</italic> An insulin pump&#x0027;s failure to deliver insulin in the right amount at the right time is a preventable cause of hospitalization. …”
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Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development by Giles Hamilton-Fletcher, Mingxin Liu, Diwei Sheng, Chen Feng, Todd E. Hudson, John-Ross Rizzo, Kevin C. Chan

“…<italic>Goal:</italic> Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). …”
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BucketAugment: Reinforced Domain Generalisation in Abdominal CT Segmentation by David Jozef Hresko, Peter Drotar

“…<italic>Goal:</italic> In recent years, deep neural networks have consistently outperformed previously proposed methods in the domain of medical segmentation. …”
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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…<italic>Goal:</italic> The purpose of this study is to evaluate the importance of cardiorespiratory variables within a Reinforcement Learning (RL) recommendation system aimed at establishing optimal strategies for drug treatment of septic patients in the intensive care unit (ICU). …”
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Analysis of GAA Junction Less NS FET Towards Analog and RF Applications at 30 nm Regime by Asisa Kumar Panigrahy, Sudheer Hanumanthakari, Shridhar B. Devamane, Shruti Bhargava Choubey, M. Prasad, D. Somasundaram, N. Kumareshan, N. Arun Vignesh, Gnanasaravanan Subramaniam, Durga Prakash M, Raghunandan Swain

“…The performance of both the classical and quantum models of the GAA nanosheet device is evaluated using the visual TCAD tool, which measures the <italic>I_ON</italic>, <italic>I_OFF</italic>, <italic>I_ON&#x002F; I_OFF</italic>, threshold voltage, DIBL, gain parameters (g_m, g_d, A_v), gate capacitance, and cut-off frequency (<italic>f_T</italic>). …”
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Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction by Ivan-Daniel Sievering, Ortal Senouf, Thabo Mahendiran, David Nanchen, Stephane Fournier, Olivier Muller, Pascal Frossard, Emmanuel Abbe, Dorina Thanou

“…<italic>Goal:</italic> In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. …”
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Gaitmap&#x2014;An Open Ecosystem for IMU-Based Human Gait Analysis and Algorithm Benchmarking by Arne Kuderle, Martin Ullrich, Nils Roth, Malte Ollenschlager, Alzhraa A. Ibrahim, Hamid Moradi, Robert Richer, Ann-Kristin Seifer, Matthias Zurl, Raul C. Simpetru, Liv Herzer, Dominik Prossel, Felix Kluge, Bjoern M. Eskofier

“…<italic>Goal:</italic> Gait analysis using inertial measurement units (IMUs) has emerged as a promising method for monitoring movement disorders. …”
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Anonymous whistleblowers reply scheme based on secret sharing by HE Kun, HUANG Yajing, DU Ruiying, SHI Min, LI Siqin, CHEN Jing

“…The experimental results show that compared to the Express scheme, the proposed scheme reduces the computational complexity during a reply to <italic>O</italic>(1) from <italic>O</italic>(log<italic>N</italic>), resulting in a 60% reduction in computational overhead for the receiving organization and a 50% reduction for the server.…”
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Fetal-BET: Brain Extraction Tool for Fetal MRI by Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus, Ali Gholipour

“…<italic>Goal:</italic> In this study, we address the critical challenge of fetal brain extraction from MRI sequences. …”
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Unveiling inverted D genes and D-D fusions in human antibody repertoires unlocks novel antibody diversity by Ponraj Prabakaran, Abhinav Gupta, Sambasiva P. Rao, Deepak Rajpal, Maria Wendt, Yu Qiu, Partha S. Chowdhury

“…Notably, our analysis revealed a broader range of D-D fusions, including D-D, D-InvD, InvD-D, and InvD-InvD configurations, opening new perspectives for antibody engineering and therapeutic development.…”
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EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload by G. Luzzani, I. Buraioli, G. Guglieri, D. Demarchi

“…<italic>Objective:</italic> The growth of autonomous systems interacting with humans leads to assessing operators&#x0027; stress and mental workload (MWL), especially in safety-critical situations. …”
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Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets by Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Mina Iravani, Pejman Farhadi Ghalati, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert

“…<italic>Goal:</italic> Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. …”
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Quantifying the Suitability of Biosignals Acquired During Surgery for Multimodal Analysis by Ennio Idrobo-Avila, Gergo Bognar, Dagmar Krefting, Thomas Penzel, Peter Kovacs, Nicolai Spicher

“…<italic>Goal:</italic> Recently, large datasets of biosignals acquired during surgery became available. …”
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