AIMC Topic: Humans

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Improving unified information extraction in Chinese mental health domain with instruction-tuned LLMs and type-verification component.

Artificial intelligence in medicine
BACKGROUND: Extracting psychological counseling help-seeker information from unstructured text is crucial for providing effective mental health support. This task involves identifying personal emotions, psychological states, and underlying psychologi...

A novel generative model for brain tumor detection using magnetic resonance imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Brain tumors are a disease that kills thousands of people worldwide each year. Early identification through diagnosis is essential for monitoring and treating patients. The proposed study brings a new method through intelligent computational cells th...

Hyperbolic multivariate feature learning in higher-order heterogeneous networks for drug-disease prediction.

Artificial intelligence in medicine
New drug discovery has always been a costly, time-consuming process with a high failure rate. Repurposing existing drugs offers a valuable alternative and reduces the risks associated with developing new drugs. Various experimental methods have been ...

C-UQ: Conflict-based uncertainty quantification-A case study in lung cancer classification.

Computers in biology and medicine
Uncertainty quantification is crucial in deep learning, especially in medical diagnostics, to measure model prediction confidence and ensure reliable clinical decisions. This study introduces a novel conflict-based uncertainty quantification approach...

Parkinson's disease tremor prediction towards real-time suppression: A self-attention deep temporal convolutional network approach.

Computers in biology and medicine
Accurate prediction of Parkinson's disease tremor (PDT) is crucial for developing assistive technologies; however, this is challenging due to the nonlinear, stochastic, and nonstationary characteristics of PDT, which substantially vary among patients...

Long-tailed medical diagnosis with relation-aware representation learning and iterative classifier calibration.

Computers in biology and medicine
Recently computer-aided diagnosis has demonstrated promising performance, effectively alleviating the workload of clinicians. However, the inherent sample imbalance among different diseases leads algorithms biased to the majority categories, leading ...

Utilizing machine learning for predicting drug release from polymeric drug delivery systems.

Computers in biology and medicine
Polymeric drug delivery systems (PDDS) play a crucial role in controlled drug release, providing improved therapeutic outcomes. However, formulating PDDS and predicting their release profiles remain challenging due to their complex structures and the...

Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.

Computers in biology and medicine
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...

Assessment of large language models in medical quizzes for clinical chemistry and laboratory management: implications and applications for healthcare artificial intelligence.

Scandinavian journal of clinical and laboratory investigation
Large language models (LLMs) have demonstrated high performance across various fields due to their ability to understand, generate, and manipulate human language. However, their potential in specialized medical domains, such as clinical chemistry and...

Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.

Journal of laparoendoscopic & advanced surgical techniques. Part A
Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely diagnosis and treatment are crucial for preventing serious morbidity and mortality. Diagnosis typically involves physical examination, laboratory tests, ...