AIMC Topic: Humans

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MR_NET: A Method for Breast Cancer Detection and Localization from Histological Images Through Explainable Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Breast cancer is the most prevalent cancer among women globally, making early and accurate detection essential for effective treatment and improved survival rates. This paper presents a method designed to detect and localize breast cancer using deep ...

Diagnosis of Pancreatic Ductal Adenocarcinoma Using Deep Learning.

Sensors (Basel, Switzerland)
Recent advances in artificial intelligence (AI) research, particularly in image processing technologies, have shown promising applications across various domains, including health care. There is a significant effort to use AI for the early diagnosis ...

Identification of metabolism related biomarkers in obesity based on adipose bioinformatics and machine learning.

Journal of translational medicine
BACKGROUND: Obesity has emerged as a growing global public health concern over recent decades. Obesity prevalence exhibits substantial global variation, ranging from less than 5% in regions like China, Japan, and Africa to rates exceeding 75% in urba...

Prediction of femoral head collapse in osteonecrosis using deep learning segmentation and radiomics texture analysis of MRI.

BMC medical informatics and decision making
BACKGROUND: Femoral head collapse is a critical pathological change and is regarded as turning point in disease progression in osteonecrosis of the femoral head (ONFH). In this study, we aim to build an automatic femoral head collapse prediction pipe...

Pharmacy students' perception and knowledge of chat-based artificial intelligence tools at a Nigerian University.

BMC medical education
BACKGROUND: Chat-based Artificial Intelligence (AI) tools, such as ChatGPT, are becoming integral to various aspects of pharmacy education. However, their integration into the curriculum faces challenges due to students' varying levels of knowledge a...

Medical students and house officers' perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is one of the sectors of medical research that is expanding the fastest right now in healthcare. AI has rapidly advanced in the field of medicine, helping to treat a variety of illnesses and reducing the numbe...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BMC gastroenterology
BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-...

Innovative label-free lymphoma diagnosis using infrared spectroscopy and machine learning on tissue sections.

Communications biology
The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinical manifestations. There is a need for inexpensive tools that require minimal expertise and are accessible for routine laboratories. Contrastingly, cu...

Optimal feature selection for heart disease prediction using modified Artificial Bee colony (M-ABC) and K-nearest neighbors (KNN).

Scientific reports
Heart disease is a complex and widespread illness that affects a significant number of people worldwide. Machine learning provides a way forward for early heart disease diagnosis. A classification model has been developed for the present study to pre...

Development and validation of preeclampsia predictive models using key genes from bioinformatics and machine learning approaches.

Frontiers in immunology
BACKGROUND: Preeclampsia (PE) poses significant diagnostic and therapeutic challenges. This study aims to identify novel genes for potential diagnostic and therapeutic targets, illuminating the immune mechanisms involved.