AIMC Topic: Humans

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Artificial Intelligence in Pancreatic Image Analysis: A Review.

Sensors (Basel, Switzerland)
Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and accurate treatment mainly rely on medical imaging, so accurate medical image analysis is especially vital for pancreatic cancer patients. However, medical ima...

Computational Insights into Reproductive Toxicity: Clustering, Mechanism Analysis, and Predictive Models.

International journal of molecular sciences
Reproductive toxicity poses significant risks to fertility and progeny health, making its identification in pharmaceutical compounds crucial. In this study, we conducted a comprehensive in silico investigation of reproductive toxic molecules, identif...

AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring.

Biosensors
The steady progress in consumer electronics, together with improvement in microflow techniques, nanotechnology, and data processing, has led to implementation of cost-effective, user-friendly portable devices, which play the role of not only gadgets ...

Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors.

BMC medical informatics and decision making
BACKGROUND: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed to develop machine learning (M...

Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BMC cancer
BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tum...

Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.

BMC medical informatics and decision making
OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models.

DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation.

BMC medical informatics and decision making
Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid cancer ranks...

What factors preventing the older adults in China from living longer: a machine learning study.

BMC geriatrics
BACKGROUND: The fact that most older people do not live long means that they do not have more time to pursue self-actualization and contribute value to society. Although there are many studies on the longevity of the elderly, the limitations of tradi...

Radiograph-based rheumatoid arthritis diagnosis via convolutional neural network.

BMC medical imaging
OBJECTIVES: Rheumatoid arthritis (RA) is a severe and common autoimmune disease. Conventional diagnostic methods are often subjective, error-prone, and repetitive works. There is an urgent need for a method to detect RA accurately. Therefore, this st...

AI-driven automatic compression system for colorectal anastomosis.

Journal of robotic surgery
Although circular staplers offer technical advancements over traditional hand-sewn techniques, their use remains challenging for unskilled users, necessitating substantial time and experience for mastery. In particular, it is challenging to apply a c...