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Machine Learning Classification of Breast Density from Bioimpedance Signals.

Breast density is a key breast cancer risk factor. It is traditionally assessed via mammography, but existing limitations invite alternative approaches. This pilot study evaluated the feasibility of machine learning-based breast density classification from Time-Domain Bioimpedance Sensing (TD-BIS) signals.

Food Classification for Swallowing Disorders Perception by Senior Population.

Texture-modified diets (TMDs) contain safe foods for individuals with dysphagia, such as soft solids or thick liquids. Considering the large population affected by dysphagia, especially older adults, it is essential to accurately measure the physical properties of these foods. The rheological and textural characteristics defined in major dysphagia guidelines-IDDSI, BDA, and the Smile Care System-are based on the experience and perception of health experts, but it is mostly unknown to which physical parameter corresponds to the classification. It is also uncertain whether older adults with dysp…

Clinically relevant pathologic classification of Congenital Cystic Lung Malformations.

Congenital cystic lung malformations encompass a diverse group of lesions that arise during in utero development. A variety of pathologic classification schemes have been proposed, but recent advances suggest that gross and microscopic morphologies can often be explained by the underlying mechanism of cyst development. A subset of congenital pulmonary airway malformations, usually with large cysts, is associated with widespread epithelial oncogenic KRAS mutation. These have a long-term risk of developing mucinous adenocarcinoma. Another subset, more commonly with smaller cysts, are associated …

Classification, functions, evolution, and applications of defective viral genomes.

Defective viral genomes (DVGs) are truncated or rearranged products derived from parental viruses during replication and they harbour numero … mechanisms of action, and the evolution of DVGs, this review provides a detailed overview of their classification methods to shed light on the characteristics of DVG formation and functions. In addition, it reviews the current detection technologies of DVGs to enable the identification and accurate quantification of DVGs. Furthermore, the discussion encompasses …

Advancements in psoriasis classification using custom transfer learning algorithms.

Psoriasis is a skin disorder which mainly occurs as a rash, scaly areas and an itchy skin. The symptoms usually occur on the chest, elbows, … tilizes ResNet50, InceptionResNetV2, and InceptionV3 with Adam and RMSprop optimizers for psoriasis classification. During training and validation, the ResNet50 model achieved good accuracy rates with values of 92.36, 84.59, and 83.55, respectively. The InceptionV2 model demonstrated impressive accuracy during training, validation, and testing, with values of 99 …

Resolution-dependent self-supervised transfer in chest radiograph classification.

BACKGROUND: Self-supervised learning (SSL) has improved visual representation learning, but its value in chest radiography remains uncertain. DINOv3 extends earlier SSL models through Gram-anchored self-distillation and explicit high-resolution adaptation. Whether these changes improve transfer learning for chest radiograph classification has not been established. METHODS: We benchmarked DINOv3 against DINOv2 and supervised ImageNet initialization across seven chest radiograph datasets comprising 816,183 radiographs from pediatric and adult cohorts. ViT-B/16 and ConvNeXt-B were evaluated unde…

Clinical classification of non-syndrome congenital ossicular chain malformations.

BACKGROUND: The existing classifications of congenital ossicular chain usually take the motility of the stapes footplate for differentiation, with a lack of attention on the concurrent malformations of facial nerve. OBJECTIVES: To explore the distribution of different types of congenital ossicular chain malformations and to propose a new classification for the guidance of clinical treatment. MATERIAL AND METHODS: Preoperative examinations and intraoperative findings of patients with congenital ossicular chain malformations from 2014 to 2025 were retrospectively collected. Based on the tradit…

metilene3: identifying DMRs across multiple conditions with auto-classification.

DNA methylation is a critical epigenetic mark across numerous species, and identifying differentially methylated regions (DMRs) is essential … ting the genome based on multiple pairwise methylation difference signals, metilene3 enables sample classification and DMR-anchored inference of epigenetic relationships. Using simulated and diverse human datasets, we show that metilene3 accurately detects DMRs, robustly clusters samples, and holds the potential to reveal new regulatory elements and sample strat …

Activity contextualisation and terrain classification via wearables in Parkinson's.

BACKGROUND: Mobility impairment is influenced by intrinsic Parkinson's disease (PD) factors but also by extrinsic/environmental factors, such as indoor vs. outdoor locations as well as terrain type. Most existing studies address human activity recognition (HAR) and terrain classification separately and often focus on healthy cohorts. There remains a need for an integrated framework that enables contextual mobility assessment in people with PD (PwPD) using wearable sensors. METHODS: In this exploratory pilot study, we developed a unified multimodal wearable framework based on a one-dimensional…

Theta and Beta1 Frequency Band Values Predict Dyslexia Classification.

Dyslexia, impacting children's reading skills, prompts families to seek cost-effective neurofeedback therapy solutions. Utilising machine learning, we identified predictive factors for dyslexia classification. Employing advanced techniques, we gathered 14-channel Quantitative Electroencephalography (QEEG) data from 200 participants, achieving 99.6% dyslexic classification accuracy through cross-validation. During validation, 48% of dyslexic children's sessions were consistently classified as normal, with a 95% confidence interval of 47.31 to 48.68. Focusing on individuals consistently diagnose…

Reconstruction of Oncologic Trachea Defects: Classification, Algorithm, and Outcomes.

OBJECTIVE: To review our experience of tracheal reconstruction for various defects and provide an algorithm for reconstruction. METHODS: All tracheal reconstruction cases from May 2002 to December 2024 were identified. Patient characteristics, types of defects, methods of reconstruction, postoperative complications, and outcomes were analyzed. RESULTS: Defects less than 4cm long were typically repaired in an end-to-end fashion (Type I, n = 72) and covered with a pedicled muscle flap, omentum, or local tissue. Longer defects (Type II) were reconstructed with a free radial forearm flap for lin

[Vertigo and oculomotor disorders: diagnosis, anatomical classification and etiology].

Dizziness and vertigo are frequent leading symptoms also in the ophthalmological practice and hospitals. They require a structured clinically oriented diagnostic approach. This article provides a practical approach based on a focused history taking using four key questions as well as a systematic examination of ocular motility (four static and four dynamic tests) and four tests assessing the vestibular system. The focus is on differentiating peripheral from central causes through structured history taking and clinical examination. In addition, the functional anatomy of the brainstem and cerebe

Therapeutic Cancer Vaccines: Classification, Mechanisms, Challenges and Future Perspectives.

BACKGROUND: With the rapid advancements in oncology, immunology, and molecular biology, immunotherapy has emerged as a cornerstone of anti-tumor treatment, complementing traditional modalities such as surgery, radiotherapy, and chemotherapy. Therapeutic cancer vaccines are a promising immunotherapy strategy that deliver tumor-associated antigens or neoantigens to prime naive T cells and generate long-lived memory cells for durable anti-tumor immunity. Recent advances in neoantigen identification, mRNA technology, biomaterial delivery and combination immunotherapy accelerate the development of

Generative Modeling and Multispectral Imaging for Eye Fundus Classification.

Background: The early diagnosis of eye fundus pathologies is crucial, as they may go unnoticed until reaching advanced stages. To offer an i … 57 × 1757 pixels). Other instances with different image resolutions and spectral ranges led to good classifications (accuracy between 96% and 98%, sensitivity between 92% and 98%, and specificity between 97% and 100%). The CVAE exhibited robust performance with convergence of the accuracy and loss through the different epochs for training and validation in all i …

Osteomyelitis: Epidemiology, Classification, Pathophysiology, Clinical Features, Diagnosis, and Management.

Osteomyelitis (OM) is a severe inflammatory bone disease caused by pathogen invasion, representing a major challenge in orthopedic surgery. … y understood. This review provides a comprehensive overview of the epidemiological characteristics, classification, clinical features, pathophysiology, and current diagnostic and therapeutic strategies for OM, with a particular focus on host immune dysregulation in disease initiation and chronicity, elucidating the mechanisms underlying immunosuppressive niche f …

Comprehensive review of thrombotic microangiopathy: classification, genetics, and management.

Thrombotic microangiopathy (TMA) comprises syndromes characterized by microangiopathic hemolytic anemia, thrombocytopenia, and organ injury, most commonly affecting the kidneys and brain. Recent advances have reframed TMAs from classical clinical labels (thrombotic thrombocytopenic purpura [TTP], hemolytic uremic syndrome, secondary TMA) toward a pathway‑based view centered on complement dysregulation, severe ADAMTS13 deficiency, and secondary endothelial injury. This review integrates current data on genetics, environmental "triggers," and clinical presentation to support a two‑hit model in w

Juvenile Sjögren disease: time for age-specific classification criteria.

OBJECTIVE: This study aims to report the clinical, laboratory, and imaging manifestations of juvenile Sjögren’s disease (SjD) and highlight the role of large salivary gland ultrasound and small salivary gland biopsy for the purpose of diagnosis and classification in this age group. BACKGROUND: Currently, there are no unified classification criteria for juvenile SjD, and pediatric-specific literature is scarce. The current literature lacks validated pediatric-specific classification and diagnostic tools. Many tests used in adult classification criteria are not routinely assessed in children bec…

AI-augmented thyroid scintigraphy for robust classification of disease.

Thyroid scintigraphy is vital for diagnosing thyroid disorders, yet deep learning (DL) models in this domain often struggle with limited, imbalanced datasets. This study investigates the impact of three data augmentation strategies including Stable Diffusion (SD), Flow Matching (FM), and Conventional Augmentation (CA), on enhancing DL-based classification of disease. Anterior thyroid scintigraphy images from 2954 patients across nine medical centers were classified into four categories: Diffuse Goiter (DG), Nodular Goiter (NG), Normal (NL), and Thyroiditis (TI). Data augmentation was performed…

Evidence for G6PD variant classification from multiplexed functional assays.

BACKGROUND: G6PD deficiency is one of the most common enzyme deficiencies worldwide, and increases the likelihood of adverse reactions to ce … ONS: Our data can be used to deepen our understanding of G6PD as a protein, and to close the gap in classification for variants of uncertain significance to improve implementation of genetic medicine for G6PD deficiency.

Классификация воздействия наркотиков с использованием графического подхода, основанного на частотности.

Классификация наркотиков в категории симптоматических (SYM) и корректирующих заболевания (DM) имеет важное значение для понимания их терапевтического воздействия и играет ключевую роль в восстановлении лекарств. В то время как многие вычислительные подходы сосредоточены на прогнозировании целевых показателей по наркотикам, они часто игнорируют характер принимаемых наркотиком мер по прогрессированию заболеваний. В этом исследовании предлагается основанная на графике стратегия классификации лекарств как SYM или DM с учетом их воздействия на лечение болезней. Мы создаем разнородную сеть, состоящу

Совпадение в аннотации оригинала
Classifying drugs into symptomatic (SYM) and disease-modifying (DM) categories is essential for understanding their therapeutic effect and p … ng genes, diseases, and drugs, and apply a guided shortest path traversal framework for drug effect classification. During this traversal, certain genes appear frequently in the shortest metapaths linking diseases and drugs. These recurrent genes are identified based on their frequency of occurrence in known drug-disease paths. For a new drug-disease pair, if th …