Resource-efficient photonic networks for next-generation AI computing.

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique strengths. The recent implementation of cellular automata in photonics demonstrates how a few local interactions can achieve high throughput and precision.

Nonlinear processing with linear optics.

Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed, the optical implementation of neural networks aims to harness the advantages of optical bandwidth and the energy efficiency of optical interconnections. In the absence of low-power optical nonlinearities, the challenge in the implementation of multilayer optical networks lies in realizing multiple optical layers without resorting to electronic components.

Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Biparametric MRI Datasets.

Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images improves the performance of a supervised learning (SL) model for prostate cancer (PCa) detection using multisite biparametric (bp) MRI datasets. Materials and Methods This retrospective study included data from 5150 patients (14 191 samples) collected across nine different imaging centers. A novel UDA method using a unified generative model was developed for PCa detection using multisite bpMRI datasets.

Increased femoral cartilage thickness in acne patients using isotretinoin: could it be a sign of early osteoarthritis?

Vitamin A derivatives have inhibitory effects on cartilage tissue, such as decreasing chondrocyte proliferation and collagen synthesis, and increasing the loss of glycosaminoglycans and proteoglycans. Therefore, isotretinoin (a vitamin A derivative) may play a role in the pathogenesis of cartilage-related diseases like osteoarthritis by affecting the balance of cartilage tissue. The aim of this study was to evaluate the distal femoral cartilage thickness in acne patients under the systemic isotretinoin therapy and to determine whether it constitutes a risk factor for the development of osteoarthritis.

Heart Failure Awareness Survey in a Turkish Population: HFAS-TR.

Objective: Heart failure is a leading cause of death and the most common diagnosis leading to hospitalization. Its awareness is lower than that of other cardiovascular diseases, both in the general population and among patients with heart failure (HF). This study aimed to establish the current level of knowledge about HF in patients with HF with reduced ejection fraction (HFrEF) and mildly reduced ejection fraction (HFmrEF) in Türkiye.

Unveiling the impact of psoriasis on liver health: does methotrexate play a villainous role?

Psoriasis might bring about an increased risk of liver diseases like nonalcoholic fatty liver disease and fibrosis. The impact of methotrexate on liver function is still a cause for concern, because of the studies suggesting an increased risk of liver damage and others finding no association. The focus of this study was the liver functions in psoriatic patients investigating the impact of long-term use of methotrexate on liver in psoriasis.

FNPC-SAM: Uncertainty-Guided False Negative/Positive Control for SAM on Noisy Medical Images.

The Segment Anything Model (SAM) is a recently developed all-range foundation model for image segmentation. It can use sparse manual prompts such as bounding boxes to generate pixel-level segmentation in natural images but struggles in medical images such as low-contrast, noisy ultrasound images. We propose a refined test-phase prompt augmentation technique designed to improve SAM's performance in medical image segmentation.

Automated Upper Tract Urothelial Carcinoma Tumor Segmentation During Ureteroscopy Using Computer Vision Techniques.

Endoscopic tumor ablation of upper tract urothelial carcinoma (UTUC) allows for tumor control with the benefit of renal preservation but is impacted by intraoperative visibility. We sought to develop a computer vision model for real-time, automated segmentation of UTUC tumors to augment visualization during treatment. We collected 20 videos of endoscopic treatment of UTUC from two institutions.

Towards navigation in endoscopic kidney surgery based on preoperative imaging.

Endoscopic renal surgeries have high re-operation rates, particularly for lower volume surgeons. Due to the limited field and depth of view of current endoscopes, mentally mapping preoperative computed tomography (CT) images of patient anatomy to the surgical field is challenging. The inability to completely navigate the intrarenal collecting system leads to missed kidney stones and tumors, subsequently raising recurrence rates.

ASSIST-U: A system for segmentation and image style transfer for ureteroscopy.

Kidney stones require surgical removal when they grow too large to be broken up externally or to pass on their own. Upper tract urothelial carcinoma is also sometimes treated endoscopically in a similar procedure. These surgeries are difficult, particularly for trainees who often miss tumours, stones or stone fragments, requiring re-operation.

Domain generalization for retinal vessel segmentation via Hessian-based vector field.

Blessed by vast amounts of data, learning-based methods have achieved remarkable performance in countless tasks in computer vision and medical image analysis. Although these deep models can simulate highly nonlinear mapping functions, they are not robust with regard to the domain shift of input data. This is a significant concern that impedes the large-scale deployment of deep models in medical images since they have inherent variation in data distribution due to the lack of imaging standardization.

In vitro antifungal susceptibility of the dermatophytes: a single center study from Eastern Black Sea Region of Turkey.

Objective: A large number of patients applying to the dermatology clinics are affected by fungal diseases, and a significant portion of which are superficial fungal infections. Dermatophyte infections are a notable public health concern and frequently encountered in clinical practice. Dermatophytosis not only compromises the quality of life but also predisposes individuals to various comorbidities due to its role as a gateway for secondary bacterial agents.

Telomerase activity and hTERT gene expression in patients with acute coronary syndrome and stable coronary artery disease.

Background: In this study, we aimed to examine the telomerase activity and hTERT gene expression in patients with acute coronary syndrome (ACS) and those with stable coronary artery disease (SCAD) and compare the results to controls. Additionally, we compared overall mortality rates relative to the telomerase activity.

Methods: A total of 211 patients (78 ACS and 71 SCAD patients) were included in the study.

Intracranial Hypertension Associated With Poly-Cranio-Radicular-Neuropathies: A Case Report and Review of the Literature.

Introduction: We present the case of a gentleman who developed rapidly progressive vision loss, ophthalmo-paresis, and flaccid quadriparesis in the context of severe intracranial hypertension. We reviewed the available cases in the literature to increase awareness of this rare clinical entity.Case Report:A 36-year-old man developed rapidly progressive vision loss, ophthalmo-paresis, and flaccid quadriparesis.

Could Blood Cell-Based Inflammatory Markers Be Used to Monitor Response to Biologic Therapy in Psoriasis?

Objectives: Despite extensive research, there is currently no specific biomarker that reliably and universally indicates treatment response in psoriasis. Multiple studies have evaluated systemic inflammation markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic immune response index (SIRI) in psoriasis patients. However, there are limited studies investigating changes in these markers with biologic therapy.

Exploring Spin Distribution and Electronic Properties in FeN-Graphene Catalysts with Edge Terminations.

Understanding the spin distribution in FeN-doped graphene nanoribbons with zigzag and armchair terminations is crucial for tuning the electronic properties of graphene-supported non-platinum catalysts. Since the spin-polarized carbon and iron electronic states may act together to change the electronic properties of the doped graphene, we provide in this work a systematic evaluation using a periodic density-functional theory-based method of the variation of spin-moment distribution and electronic properties with the position and orientation of the FeN defects, and the edge terminations of the graphene nanoribbons. Antiferromagnetic and ferromagnetic spin ordering of the zigzag edges were considered.

COSST: Multi-Organ Segmentation With Partially Labeled Datasets Using Comprehensive Supervisions and Self-Training.

Deep learning models have demonstrated remarkable success in multi-organ segmentation but typically require large-scale datasets with all organs of interest annotated. However, medical image datasets are often low in sample size and only partially labeled, i.e.

Analysis of treatment adherence in patients undergoing phototherapy.

Objective: Phototherapy is a convenient and effective treatment alternative for a range of skin diseases. However, a major challenge in patient adherence to phototherapy may be the necessity of visiting a phototherapy center regularly over an extended period of time. The aims of this study were (i) to investigate the adherence rate to phototherapy and (ii) to determine factors associated with adherence to narrow-band ultraviolet B phototherapy (nbUVB) treatment.

Relationship between psoriasis and urolithiasis.

The aim of the present study was to investigate whether patients with psoriasis are prone to urolithiasis. Prospective analysis of 67 patients diagnosed as psoriasis (PS group) and 65 volunteers who had never been diagnosed as psoriasis (NPS group) was performed. The levels of oxalate, citrate, calcium, uric acid, magnesium, creatinine, and sodium were evaluated by analyzing the 24-h urine samples.

Evaluation of atherosclerotic risk in rosacea patients through serum fetuin-A and carotid intima media thickness.

Background: The link between rosacea and various systemic conditions has been growing in prominence, even though the relationship between rosacea and cardiovascular disease remains a subject of debate in current research.

Aims: Detecting the connection between rosacea and subclinical atherosclerosis using laboratory and ultrasonographic parameters.

Methods: Fifty rosacea patients and 49 control were included in the study.

Forward-forward training of an optical neural network.

Neural networks (NNs) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations. Optics-based platforms, using technologies such as silicon photonics and spatial light modulators, offer promising avenues for achieving this goal. However, training multiple programmable layers together with these physical systems poses challenges, as they are difficult to fully characterize and describe with differentiable functions, hindering the use of error backpropagation algorithm.

Do Trade and Financial Cooperation Improve Environmentally Sustainable Development: A Distinction Between and Globalization.

The adoption of growth strategies based on foreign trade, especially in the previous century when liberal policies began to dominate, is one of the main reasons for the increase in output and indirectly for environmental concerns. On the other hand, there are complex claims about the environmental effects of liberal policies and thus of globalization. This study intends to analyze the effects of global collaborations involving 11 transition economies that have completed the transition process on the environmentally sustainable development of these nations.