AIMC Topic: Humans

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Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy.

Scientific reports
Prostate cancer remains a significant public health concern, with a substantial proportion of patients experiencing biochemical recurrence (BCR) after radical prostatectomy (RP). Traditional risk models, such as CAPRA-S, have demonstrated moderate pr...

Integrating artificial intelligence and optogenetics for Parkinson's disease diagnosis and therapeutics in male mice.

Nature communications
Parkinson's disease (PD), a progressive neurodegenerative disorder, presents complex motor symptoms and lacks effective disease-modifying treatments. Here we show that integrating artificial intelligence (AI) with optogenetic intervention, termed opt...

CT-based machine learning model integrating intra- and peri-tumoral radiomics features for predicting occult lymph node metastasis in peripheral lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate preoperative assessment of occult lymph node metastasis (OLNM) plays a crucial role in informing therapeutic decision-making for lung cancer patients. Computed tomography (CT) is the most widely used imaging modality for preopera...

Artificial intelligence-based prediction of treatment failure and medication non-adherence in overactive bladder management.

BMC urology
BACKGROUND: Overactive bladder management presents significant challenges, with treatment failures and medication non-adherence posing substantial barriers to patient outcomes. Early prediction of these challenges could enable timely interventions an...

Development and verification of a convolutional neural network-based model for automatic mandibular canal localization on multicenter CBCT images.

BMC oral health
OBJECTIVES: Development and verification of a convolutional neural network (CNN)-based deep learning (DL) model for mandibular canal (MC) localization on multicenter cone beam computed tomography (CBCT) images.

GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data.

BMC genomics
BACKGROUND: Single-cell RNA sequencing analysis faces critical challenges including high dimensionality, sparsity, and complex topological relationships between cells. Current methods struggle to simultaneously preserve global structure, model cellul...

A novel and efficient personalized stress detection technique using a deep learning model.

Scientific reports
Stress is a type of mental tension or escalated psycho-physiological state of the human body caused by a problematic situation. It majorly affects adults and elders, which further leads to chronic health problems and heart-related diseases. Various t...

Integrating non-linear radon transformation for diabetic retinopathy grading.

Scientific reports
Diabetic retinopathy is a serious ocular complication that poses a significant threat to patients' vision and overall health. Early detection and accurate grading are essential to prevent vision loss. Current automatic grading methods rely heavily on...

Racial and socioeconomic disparities in long term survival after surgery and radiation for spinal cord hemangioblastoma.

Scientific reports
Spinal cord hemangioblastomas are rare, benign, intradural tumors that, despite their nonmalignant histopathology, can lead to substantial neurological morbidity. While disparities in outcomes based on race and socioeconomic status have been well-doc...

Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis.

Scientific reports
The accurate classification of obesity is essential for public health and clinical decision-making. Traditional anthropometric measures such as body mass index (BMI) have limitations in differentiating between fat and lean mass. This study aimed to e...