AIMC Topic: Humans

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Tumor-on-chip's alliance with molecular pathology against metastatic disease.

Journal of biomedical science
BACKGROUND: Cancer is the second leading cause of death worldwide. While significant progress has been made in early detection and treatment, metastasis remains the major cause of cancer-related morbidity and mortality. In the last decade the rate of...

Accuracy of AI-based raman spectroscopy in the diagnosis of gastric cancer: a systematic review and meta-analysis.

Lasers in medical science
Gastric cancer (GC) remains a significant global health challenge with high mortality rates, often due to late-stage diagnosis. We hypothesize that Raman spectroscopy (RS) (a modern minimally invasive technique that uses light to analyze the molecula...

Optimizing and evaluating robustness of AI for brain metastasis detection and segmentation via loss functions and multi-dataset training.

Biomedical physics & engineering express
. Accurate detection and segmentation of brain metastases (BM) from MRI are critical for the appropriate management of cancer patients. This study investigates strategies to enhance the robustness of artificial intelligence (AI)-based BM detection an...

Morphological and textural descriptors analysis of digital mammograms with radiological findings to support breast cancer detection using artificial neural networks.

Biomedical physics & engineering express
. To classify digital mammograms based on radiological findings using morphology and texture descriptors with artificial neural networks (ANN) for breast cancer detection.The mammography dataset from High Specialty Regional Hospital of Oaxaca (HRAEO)...

Automated retinal disease classification using deep learning and AlexNet with statistical models analysis.

PloS one
Diabetic Retinopathy, Cataract, and Glaucoma are major retinal diseases that require early detection to prevent irreversible vision loss. This study proposes a deep learning-based framework for the automated classification of retinal images into four...

Integrative multi-omics and network-based machine learning for early diagnosis of Parkinson's disease.

PloS one
BACKGROUND: Accurate diagnosis of Parkinson's Disease (PD) remains challenging due to its biological complexity. Integrating machine learning with multi-omics and network topological analyses may enhance diagnostic precision.

Representativeness of a German AI-enabled data network for secondary epidemiological analysis based on electronic health records.

PloS one
INTRODUCTION: The ongoing digitalization of medicine, increased computing power and low-cost storage capacities enable the use of AI-based algorithms for epidemiological big data analysis of electronic patient records. The aim of this study was to ev...

Including patient experiences from online sources in guidelines: A natural language processing study on scabies.

PloS one
OBJECTIVE: Including patients' experience-based knowledge in the development of clinical and public health guidelines has been shown to enhance the quality, relevance, and applicability of guidelines. However, the meaningful and methodologically soun...

Machine learning for screening laryngopharyngeal reflux symptoms in college students: a cross-sectional study.

Annals of medicine
BCKGROUND: Laryngopharyngeal reflux (LPR) is a widespread global health issue. Its recurring symptoms and impact on quality of life create significant economic burdens for individuals and society. To examine the links between lifestyle, diet, and LPR...

Magnetically Driven Lasing Microrobots for Precise Photodynamic Therapy.

ACS nano
Photodynamic therapy (PDT) is an emerging approach for tumor treatment, valued for its noninvasive and stimuli-responsive properties. However, its therapeutic efficacy is often constrained by unintended damage to healthy tissues, largely due to the s...