AIMC Topic: Humans

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Robust one-class support vector machine.

Neural networks : the official journal of the International Neural Network Society
One-Class Support Vector Machine (OCSVM) is an effective algorithm in one-class classification task. However, it exhibits sensitivity to noise and outliers. Current solutions often employ bounded loss functions that impose finite but relatively large...

CCA: Contrastive cluster assignment for supervised and semi-supervised medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Transformers have shown great potential in vision tasks such as semantic segmentation. However, most of the existing transformer-based segmentation models neglect the cross-attention between pixel features and class features which impedes the applica...

SuperM2M: Supervised and mixture-to-mixture co-learning for speech enhancement and noise-robust ASR.

Neural networks : the official journal of the International Neural Network Society
The current dominant approach for neural speech enhancement is based on supervised learning by using simulated training data. The trained models, however, often exhibit limited generalizability to real-recorded data. To address this, this paper inves...

Cesarean Scar Pregnancy Prognostic Classification System Based on Machine-Learning and Traditional Linear Scoring Models.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Cesarean scar pregnancy (CSP) refers to a special type of pregnancy with a variable prognosis. We aimed to establish a prognostic classification system using ultrasound and clinical features to provide a reference for management strategie...

Advancements in small molecule fluorescent probes for the detection of formaldehyde in environmental and food samples: A comprehensive review.

Food chemistry
Formaldehyde (FA), a hazardous substance with carcinogenicity and mutagenicity, necessitates sensitive and accurate detection methods for protecting public health and the environment. While numerous reviews have explored FA fluorescent probes, the cu...

Interpretable machine learning-based insights into early-life endocrine disruptor exposure and small vulnerable newborns.

Journal of hazardous materials
Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newborns, including conditions such as being small for gestational age (SGA) and preterm birth (PTB), yet evidence remains limited. This study, which is b...

Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancing quality of life (QoL) is the primary therapeutic objective. Clinicians tailor their treatment strategy by weighing the QoL benefits against expected...

A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).

False Crisis Alarms in Cardiopulmonary Monitoring:: Identification, Causes, and Clinical Implications.

Critical care nursing clinics of North America
The systematic annotation of crisis alarms reveals a high number of false alarms for both ventricular tachycardia and asystole, which are best identified by inspecting simultaneous multilead electrocardiographs. Among the few true crisis alarms, 11 w...