AIMC Topic: Humans

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Machine learning developed regulatory T cells-related signature for prognosis and immunotherapy benefit in oral squamous cell carcinoma.

American journal of otolaryngology
BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common malignancies with poor clinical outcome. Regulatory T cells (Tregs) have a dual role in maintaining immune homeostasis and suppressing anti-tumor immunity. The role of Tregs re...

Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.

Frontiers in cellular and infection microbiology
BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipterous larvae (maggots). However, bibliometric analysis of this disease remains sparse. Machine learn...

The Role of Computed Tomography and Artificial Intelligence in Evaluating the Comorbidities of Chronic Obstructive Pulmonary Disease: A One-Stop CT Scanning for Lung Cancer Screening.

International journal of chronic obstructive pulmonary disease
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Comorbidities in patients with COPD significantly increase morbidity, mortality, and healthcare costs, posing a significant burden on the management o...

Application of machine learning in predicting consumer behavior and precision marketing.

PloS one
with the intensification of market competition and the complexity of consumer behavior, enterprises are faced with the challenge of how to accurately identify potential customers and improve user conversion rate. This paper aims to study the applicat...

Electrochemical microfluidic biosensors for the detection of cancer biomarker miRNAs.

Talanta
Cancer is a formidable adversary in contemporary healthcare. Routine screening and early diagnosis are crucial for favourable therapeutic outcomes. Publications, clinical trials, and patent landscape analysis suggest miRNA as promising biomarkers for...

Evaluating Large Language Models in Addressing Patient Questions on Endodontic Pain: A Comparative Analysis of Accessible Chatbots.

Journal of endodontics
INTRODUCTION: Patients increasingly use large language models for health-related information, but their reliability and usefulness remain controversial. Continuous assessment is essential to evaluate their role in patient education. This study evalua...

SAMSnake: A generic contour-based instance segmentation network assisted by Efficient Segment Anything Model.

Neural networks : the official journal of the International Neural Network Society
Contour-based instance segmentation has gained significant attention due to its efficiency and ability to produce precise segmentation boundaries. In this paper, we propose SAMSnake, a novel contour-based instance segmentation network. Our method int...

Interpretable Prognostic Modeling for Postoperative Pancreatic Cancer Using Multi-machine Learning and Habitat Radiomics: A Multi-center Study.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate risk stratification is critical for guiding personalized treatment in resectable pancreatic cancer (RPC). This retrospective study assessed the utility of habitat radiomics for predicting recurrence-free survival (R...

Associations between the 24-h Activity Daily Cycle and Incident Dementia.

Medicine and science in sports and exercise
BACKGROUND: Physical activity, sedentary behavior (SB), and sleep all impact the risk of incident dementia, however, engagement in these activities is constrained by the 24-h day. Increasing time spent in one activity necessarily reduces time spent i...

Prediction of EGFR Mutations in Lung Adenocarcinoma via CT Images: A Comparative Study of Intratumoral and Peritumoral Radiomics, Deep Learning, and Fusion Models.

Academic radiology
RATIONALE AND OBJECTIVES: This study aims to analyze the intratumoral and peritumoral characteristics of lung adenocarcinoma patients on the basis of chest CT images via radiomic and deep learning methods and to develop and validate a multimodel fusi...