AIMC Topic: Female

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The melanoma MEGA-study: Integrating proteogenomics, digital pathology, and AI-analytics for precision oncology.

Journal of proteomics
Melanoma remains the most aggressive form of skin cancer, characterized by high metastatic potential, genetic heterogeneity, and resistance to conventional therapies. The Melanoma MEGA-Study is a multi-center initiative designed to address these clin...

Multimodal personalization of transcranial direct current stimulation for modulation of sensorimotor integration.

NeuroImage
Transcranial direct current stimulation (tDCS) for the modulation of smooth pursuit eye movements provides an ideal model for investigating sensorimotor integration. Within neural networks subserving smooth pursuit, visual area V5 is a core hub where...

Peripersonal and extrapersonal space encoding in virtual reality: Insights from an fMRI study.

NeuroImage
The brain processes objects in reachable peripersonal space and non-reachable extrapersonal space in different neural networks. In contrast to extrapersonal space, spatial processing in peripersonal space is linked to the activation of affordances in...

Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Life sciences
Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However, assessing the clinical efficacy of chemotherapy drugs remains a challenging task. In recent years, ...

Machine learning methods for sex estimation of sub-adults using cranial computed tomography images.

Anthropologischer Anzeiger; Bericht uber die biologisch-anthropologische Literatur
This research aimed to compare the classification accuracy of three machine learning (ML) methods (random forest (RF), support vector machines (SVM), linear discriminant analysis (LDA)) for sex estimation of sub-adults using cranial computed tomograp...

[Development of a machine learning-based diagnostic model for T-shaped uterus using transvaginal 3D ultrasound quantitative parameters].

Zhonghua yi xue za zhi
To develop a machine learning diagnostic model for T-shaped uterus based on quantitative parameters from 3D transvaginal ultrasound. A retrospective cross-sectional study was conducted, recruiting 304 patients who visited the hysteroscopy centre of...

ML-STIM: Machine Learning for SubThalamic nucleus Intraoperative Mapping.

Journal of neural engineering
Deep Brain Stimulation (DBS) of the SubThalamic Nucleus (STN) is effective in alleviating motor symptoms in medication-refractory patients with Parkinson's Disease (PD). Intraoperative identification of the STN relies on MicroElectrode Recordings (ME...

The oral microbiome and its effect on exhaled breath volatile analysis-the elephant in the room.

Journal of breath research
The rapid transfer of volatiles from alveolar blood into the lungs and then out of the body in exhaled breath leads to the common and natural conclusion that these volatiles provide information on health and metabolic processes, with considerable pot...

Machine learning in diagnosing coronary artery disease via optical pumped magnetometer magnetocardiography: a prospective cohort study.

Physiological measurement
The potential of optical pumped magnetometer magnetocardiography (OPM-MCG) for diagnosing coronary artery disease (CAD) has been initially shown, yet lacks large-scale prospective research.Using invasive coronary angiography (ICA) as a reference, we ...

Tumor-Intrinsic and Microenvironmental Determinants of Impaired Antitumor Immunity in Chromophobe Renal Cell Carcinoma.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: While immune checkpoint inhibition (ICI) has transformed the management of many advanced renal cell carcinomas (RCCs), the determinants of effective antitumor immunity for chromophobe RCC (ChRCC) and renal oncocytic tumors remain an unmet cl...