A novel hybridized feature extraction approach for lung nodule classification based on transfer learning technique by P Malin Bruntha, S Immanuel Alex Pandian, J Anitha, Siril Sam Abraham, S Niranjan Kumar

“…Purpose: In the field of medical diagnosis, deep learning-based computer-aided detection of diseases will reduce the burden of physicians in the diagnosis of diseases especially in the case of lung cancer nodule classification. …”
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Polymeric biomaterials for biophotonic applications by Dingying Shan, Ethan Gerhard, Chenji Zhang, John William Tierney, Daniel Xie, Zhiwen Liu, Jian Yang

“…With the growing importance of optical techniques in medical diagnosis and treatment, there exists a pressing need to develop and optimize materials platform for biophotonic applications. …”
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A Multi-Chamber Paper-Based Platform for the Detection of Amyloid β Oligomers 42 via Copper-Enhanced Gold Immunoblotting by Le-Minh-Tu Phan, Sungbo Cho

“…However, the application of these complicated biosensors is limited in medical diagnosis, due to the difficulties in robust sensing platform development, high costs, and the necessity for technical professionals. …”
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The Structural Properties of Odorants Modulate Their Association to Human Odorant Binding Protein by Tarsila G. Castro, Carla Silva, Teresa Matamá, Artur Cavaco-Paulo

“…Understanding how the odorants behave when complexed with the OBP in human olfaction opens new possibilities for the development of future biotechnological applications, including sensory devices, medical diagnosis, among others.…”
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Application Progress of the Single Domain Antibody in Medicine by Huaping Tang, Yuan Gao, Jiangyuan Han

“…As a new generation of nano-biological tools, natural and synthetic nanobodies have been used in many fields of biomedicine, including biomolecular materials, biological research, medical diagnosis and immune therapies. This article briefly overviews the biomolecular structure, biochemical properties, immune acquisition and phage library construction of nanobodies and comprehensively reviews their applications in medical research. …”
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Psychopathology and Somatic Complaints: A Cross-Sectional Study with Portuguese Adults by Joana Proença Becker, Rui Paixão, Manuel João Quartilho

“…(1) Background: Functional somatic symptoms (FSS) are physical symptoms that cannot be fully explained by medical diagnosis, injuries, and medication intake. More than the presence of unexplained symptoms, this condition is associated with functional disabilities, psychological distress, increased use of health services, and it has been linked to depressive and anxiety disorders. …”
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Comparing the Robustness of ResNet, Swin-Transformer, and MLP-Mixer under Unique Distribution Shifts in Fundus Images by Kazuaki Ishihara, Koutarou Matsumoto

“…Safety-critical applications employed in medical diagnosis must be robust to distribution shifts. …”
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Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions by Beatriz Garcia Santa Cruz, Andreas Husch, Frank Hertel

“…The main challenges in applying ML to medical diagnosis and its implications for PD are also addressed, including current limitations for safe translation into hospitals. …”
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Integrated the Medical Procedure Analyze Seismic Resilience of Healthcare System: A Critical Review from the Resilience of Healthcare System vs. Medical Demand Perspective by Bin Liang, Qian Tao, Wuping Gao, Quanchang Ren, Xinqiang Yao

“…Many studies have applied resilience research to address critical issues in the medical rescue of postearthquake casualties, such as medical diagnosis, emergency surgery, and intensive care. …”
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Vitamin D, men's health and male reproduction by I. A. Tyuzikov, S. Yu. Kalinchenko, L. O. Vorslov, Yu. A. Tishova

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Comparison of the Capacity of Several Machine Learning Tools to Assist Immunofluorescence-Based Detection of Anti-Neutrophil Cytoplasmic Antibodies by Daniel Bertin, Pierre Bongrand, Nathalie Bardin

“…The success of artificial intelligence and machine learning is an incentive to develop new algorithms to increase the rapidity and reliability of medical diagnosis. Here we compared different strategies aimed at processing microscope images used to detect anti-neutrophil cytoplasmic antibodies, an important vasculitis marker: (i) basic classifier methods (logistic regression, k-nearest neighbors and decision tree) were used to process custom-made indices derived from immunofluorescence images yielded by 137 sera. …”
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Development of A User-Centered Design Framework for Palliative and Hospice Care Patients for a Better Quality of Life Experience by Shahira Assem Abdel-Razek

“…Amongst those that are often “left behind” are patients at the end stage of their life due to a terminal illness or a medical diagnosis. These are often left to die without thought to the quality of life that they receive before their demise, and many experience this stage at home due to fear of expenses, or in a best-case scenario at a hospital to help alleviate or manage pain. …”
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Recent Advances in Tracking Devices for Biomedical Ultrasound Imaging Applications by Chang Peng, Qianqian Cai, Mengyue Chen, Xiaoning Jiang

“…Recent development in tracking technology has led to increased accuracy and intuitiveness of ultrasound imaging and navigation with less reliance on operator skills, thereby benefiting the medical diagnosis and treatment. Although commercially available tracking systems are capable of achieving sub-millimeter resolution for positional tracking and sub-degree resolution for orientational tracking, such systems are subject to a number of disadvantages, including high costs and time-consuming calibration procedures. …”
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An Investigation of Transfer Learning Approaches to Overcome Limited Labeled Data in Medical Image Analysis by Jinyeong Chae, Jihie Kim

“…A significant amount of research has investigated automating medical diagnosis using deep learning. However, because medical data are collected through diagnostic tests, deep learning methods used in existing studies have had a disadvantage in that the number of training samples is insufficient and the labeling cost is high. …”
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Dynamic activation and enhanced image contour features for object detection by Jun Wu, Jiahui Zhu, Xin Tong, Tianliang Zhu, Tianyi Li, Chunzhi Wang

“…Object detection technology is a popular research direction which is widely used in areas such as autonomous driving and medical diagnosis. At this stage mobile devices often have limited storage resources to deploy large object detection networks and need to meet real-time requirements. …”
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Diagnosis of Lung Cancer Disease Based on Back-Propagation Artificial Neural Network Algorithm by Hanan Akkar, Suhad Qasim Haddad

“…So , algorithms that are related with computer vision and Image processing are extremely important for early medical diagnosis of lung cancer. In current work ( ) computed tomography scan images were collected from several patients Classification was done using Back Propagation Artificial Neural Network ( ).It is considered as a powerful artificially intelligent technique with training rule for optimization to update the weights of the overall connections in order to determine the abnormal image. …”
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Microwave imaging for watermelon maturity determination by Joe Garvin, Feras Abushakra, Zachary Choffin, Bayley Shiver, Yu Gan, Lingyan Kong, Nathan Jeong

“…Microwave imaging technology is a useful method often applied in medical diagnosis and can be used by the food industry to ensure food safety and quality. …”
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New Hybrid Graph Convolution Neural Network with Applications in Game Strategy by Hanyue Xu, Kah Phooi Seng, Li-Minn Ang

“…Deep convolutional neural networks (DCNNs) have enjoyed much success in many applications, such as computer vision, automated medical diagnosis, autonomous systems, etc. Another application of DCNNs is for game strategies, where the deep neural network architecture can be used to directly represent and learn strategies from expert players on different sides. …”
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Survey on vertical federated learning: algorithm, privacy and security by Jinyin CHEN, Rongchang LI, Guohan HUANG, Tao LIU, Haibin ZHENG, Yao CHENG

“…Federated learning （FL） is a distributed machine learning technology that enables joint construction of machine learning models by transmitting intermediate results （e.g., model parameters, parameter gradients, embedding representation, etc.） applied to data distributed across various institutions.FL reduces the risk of privacy leakage, since raw data is not allowed to leave the institution.According to the difference in data distribution between institutions, FL is usually divided into horizontal federated learning （HFL）, vertical federated learning （VFL）, and federal transfer learning （TFL）.VFL is suitable for scenarios where institutions have the same sample space but different feature spaces and is widely used in fields such as medical diagnosis, financial and security of VFL.Although VFL performs well in real-world applications, it still faces many privacy and security challenges.To the best of our knowledge, no comprehensive survey has been conducted on privacy and security methods.The existing VFL was analyzed from four perspectives: the basic framework, communication mechanism, alignment mechanism, and label processing mechanism.Then the privacy and security risks faced by VFL and the related defense methods were introduced and analyzed.Additionally, the common data sets and indicators suitable for VFL and platform framework were presented.Considering the existing challenges and problems, the future direction and development trend of VFL were outlined, to provide a reference for the theoretical research of building an efficient, robust and safe VFL.…”
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Automatic Facial Palsy Detection—From Mathematical Modeling to Deep Learning by Eleni Vrochidou, Vladan Papić, Theofanis Kalampokas, George A. Papakostas

“…Automated solutions for medical diagnosis based on computer vision form an emerging field of science aiming to enhance diagnosis and early disease detection. …”
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