Academic Articles & Research Papers

Small cell neuroendocrine carcinoma of the cervix: From molecular basis to therapeutic advances

Small cell neuroendocrine carcinoma of the cervix (SCNECC) is an uncommon but aggressive uterine malignancy, the cause of which is generally associated with human papillomavirus (HPV) infection. A lack of clinical trials and evidence-based ...

Characteristics of pulmonary microvascular structure in postnatal yaks

Abstract Yaks are typical plateau-adapted animals, however the microvascular changes and characteristics in their lungs after birth are still unclear. Pulmonary microvasculature characteristics and changes across age groups were analysed us...

Molecular Chaperone GRP94/GP96 in Cancers: Oncogenesis and Therapeutic Target

During tumor development and progression, intrinsic and extrinsic factors trigger endoplasmic reticulum (ER) stress and the unfolded protein response, resulting in the increased expression of molecular chaperones to cope with the stress and...

High posterior tibial slope increases anterior cruciate ligament elongation in unicompartmental knee arthroplasty during early-flexion of lunge

Abstract Background In-silico and in-vitro studies have revealed an appropriate posterior tibial slope (PTS) is critical for normal anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) tension and knee biomechanical behavi...

Genomic Organization and Expression of Iron Metabolism Genes in the Emerging Pathogenic Mold Scedosporium apiospermum

The ubiquitous mold Scedosporium apiospermum is increasingly recognized as an emerging pathogen, especially among patients with underlying disorders such as immunodeficiency or cystic fibrosis (CF). Indeed, it ranks the second among the fil...

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

BackgroundNatural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and incr...

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

The long non-coding RNA LINC00152 is essential for cell cycle progression through mitosis in HeLa cells

Abstract In recent years, long non-coding RNA (lncRNA) research has identified essential roles of these transcripts in virtually all physiological cellular processes including tumorigenesis, but their functions and molecular mechanisms are ...

Assessment of algorithmic performance in PET-CT segmentation of solitary lung tumors.

Radiomics and deep learning in lung cancer

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

Deep learning in medical image registration: a review

This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into se...

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Abstract Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite pr...

Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function

Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...

MWG-UNet: Hybrid Deep Learning Framework for Lung Fields and Heart Segmentation in Chest X-ray Images

Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability...

A deep-learning system to classify lung X-ray images into normal/pneumonia class

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...

Towards a physics informed digital twin to predict cerebral blood flow and cerebral vascular regulation

Abstract Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure and physiological mechanisms collectively referred to as cerebral vascular regulation (CVR). Direct measurement of cerebral blood fl...

Quantifying the incremental value of deep learning: Application to lung nodule detection.

We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some...