AIMC Topic: Humans

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Thermal Time Constant CNN-Based Spectrometry for Biomedical Applications.

Sensors (Basel, Switzerland)
This paper presents a novel method based on a convolutional neural network to recover thermal time constants from a temperature-time curve after thermal excitation. The thermal time constants are then used to detect the pathological states of the ski...

Biophysical Profiling of Sickle Cell Disease Using Holographic Cytometry and Deep Learning.

International journal of molecular sciences
Sickle cell disease (SCD) is an inherited hematological disorder associated with high mortality rates, particularly in sub-Saharan Africa. SCD arises due to the polymerization of sickle hemoglobin, which reduces flexibility of red blood cells (RBCs),...

Deep learning-based diagnosis of histopathological patterns for invasive non-mucinous lung adenocarcinoma using semantic segmentation.

BMJ open
OBJECTIVES: The application of artificial intelligence (AI) to the field of pathology has facilitated the development of digital pathology, hence, making AI-assisted diagnosis possible. Due to the variety of lung cancers and the subjectivity of manua...

ChatGPT vs Google for Queries Related to Dementia and Other Cognitive Decline: Comparison of Results.

Journal of medical Internet research
BACKGROUND: People living with dementia or other cognitive decline and their caregivers (PLWD) increasingly rely on the web to find information about their condition and available resources and services. The recent advancements in large language mode...

Deep learning-based multiomics integration model for predicting axillary lymph node metastasis in breast cancer.

Future oncology (London, England)
To develop a deep learning-based multiomics integration model. Five types of omics data (mRNA, DNA methylation, miRNA, copy number variation and protein expression) were used to build a deep learning-based multiomics integration model a deep neura...

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Neonatology
Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the scree...

Virtual screening strategy for anti-DPP-IV natural flavonoid derivatives based on machine learning.

Journal of biomolecular structure & dynamics
Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to seve...

SVM-RFE enabled feature selection with DMN based centroid update model for incremental data clustering using COVID-19.

Computer methods in biomechanics and biomedical engineering
This research introduces an efficacious model for incremental data clustering using Entropy weighted-Gradient Namib Beetle Mayfly Algorithm (NBMA). Here, feature selection is done based upon support vector machine recursive feature elimination (SVM-R...

Application of Semi-supervised Fuzzy Clustering Based on Knowledge Weighting and Cluster Center Learning to Mammary Molybdenum Target Image Segmentation.

Interdisciplinary sciences, computational life sciences
Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large,...