WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval.

The paper proposes a federated content-based medical image retrieval (FedCBMIR) tool that utilizes federated learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. CBMIR is a tool to find the most similar cases in the data set to assist pathologists. Training such a tool necessitates a pool of whole-slide images (WSIs) to train the feature extractor (FE) to extract an optimal embedding vector.

Improving the quality of image generation in art with top-k training and cyclic generative methods.

The creation of artistic images through the use of Artificial Intelligence is an area that has been gaining interest in recent years. In particular, the ability of Neural Networks to separate and subsequently recombine the style of different images, generating a new artistic image with the desired style, has been a source of study and attraction for the academic and industrial community. This work addresses the challenge of generating artistic images that are framed in the style of pictorial Impressionism and, specifically, that imitate the style of one of its greatest exponents, the painter Claude Monet.

A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models.

Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the diagnostic uncertainty remains until now, especially in the intermediate category known as Spitz tumor of unknown malignant potential (STUMP) or atypical Spitz tumor. Studies developing deep learning (DL) models to diagnose melanocytic tumors using whole slide imaging (WSI) are scarce, and few used ST for analysis, excluding STUMP.

Comparing Robotic-Assisted to Open Radical Cystectomy in the Management of Non-Muscle-Invasive Bladder Cancer: A Propensity Score Matched-Pair Analysis.

Background: For non-muscle-invasive bladder cancer (NMIBC) requiring radical surgery, limited data are available comparing robotic-assisted radical cystectomy with intracorporeal urinary diversion (iRARC) to open radical cystectomy (ORC). The objective of this study was to compare the two surgical techniques.

Methods: A multicentric cohort of 593 patients with NMIBC undergoing iRARC or ORC between 2015 and 2020 was prospectively gathered.

Deep learning system for classification of ploidy status using time-lapse videos.

Objective: To develop a spatiotemporal model for de prediction of euploid and aneuploid embryos using time-lapse videos from 10-115 hours after insemination (hpi).

Design: Retrospective study.

Main Outcome Measures: The research used an end-to-end approach to develop an automated artificial intelligence system capable of extracting features from images and classifying them, considering spatiotemporal dependencies.

ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis.

Background And Objective: Prostate cancer is one of the most common diseases affecting men. The main diagnostic and prognostic reference tool is the Gleason scoring system. An expert pathologist assigns a Gleason grade to a sample of prostate tissue.

Minding the gap: Evidence, implementation and funding gaps in mental health services delivery for school-aged children.

State and local educational agencies are grappling with growing mental health needs among school-aged children that intensified during the COVID-19 pandemic. We undertake a case study of the experiences of one state, Tennessee, to examine the landscape of mental health interventions that are being deployed and to illuminate contextual factors that can support their implementation or exacerbate state and local challenges in addressing children's fast-rising mental health needs. We begin with an examination of the knowledge base on interventions and approaches that are commonly employed in K-12 schools to address children's mental health needs, including in Tennessee, with the aim to identify notable gaps in what we understand about their implementation and impacts on student outcomes.

Age represents the main driver of surgical decision making in patients candidate to radical cystectomy.

Background And Objectives: Age might influence the choice of surgical approach, type of urinary diversion (UD) and lymph node dissection (LND) in patients candidate to radical cystectomy (RC) for urothelial bladder cancer (UBC). Similarly, age may enhance surgical morbidity and worsen perioperative outcomes. We tested the impact of age (octogenarian vs.

Do perioperative blood transfusions impact oncological outcomes of robot-assisted radical cystectomy with intracorporeal urinary diversion? Results from a large multi-institutional registry.

Background: Blood transfusions (BT) have been associated with adverse oncologic outcomes in multiple malignancies including open radical cystectomy (ORC) for urothelial carcinoma of the bladder (UCB). Robot-assisted radical cystectomy (RARC) with intracorporeal urinary diversion (ICUD) delivers similar oncologic outcomes compared to ORC, yet with lower blood loss and reduced transfusions. However, the impact of BT after robotic cystectomy is still unknown.

Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review.

The rise of Artificial Intelligence (AI) has shown promising performance as a support tool in clinical pathology workflows. In addition to the well-known interobserver variability between dermatopathologists, melanomas present a significant challenge in their histological interpretation. This study aims to analyze all previously published studies on whole-slide images of melanocytic tumors that rely on deep learning techniques for automatic image analysis.

Constrained multiple instance learning for ulcerative colitis prediction using histological images.

Background And Objective: Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) affecting the colon and the rectum characterized by a remitting-relapsing course. To detect mucosal inflammation associated with UC, histology is considered the most stringent criteria. In turn, histologic remission (HR) correlates with improved clinical outcomes and has been recently recognized as a desirable treatment target.

Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques.

Background: Embryo morphology is a predictive marker for implantation success and ultimately live births. Viability evaluation and quality grading are commonly used to select the embryo with the highest implantation potential. However, the traditional method of manual embryo assessment is time-consuming and highly susceptible to inter- and intra-observer variability.

Comparison of various late gadolinium enhancement magnetic resonance imaging methods with high-definition voltage and activation mapping for detection of atrial cardiomyopathy.

Aims: Atrial cardiomyopathy (ACM) is associated with increased arrhythmia recurrence rates after pulmonary vein isolation (PVI). We compare the most common left atrial (LA) late gadolinium enhancement magnetic resonance imaging (LGE-MRI)-methods [Utah-method and image intensity ratio (IIR)-methods] and endocardial voltage mapping for ACM-detection and outcome prediction after PVI for atrial fibrillation (AF).

Methods And Results: In this prospective observational study, 37 ablation-naive patients (66 ± 9 years, 84% male) with persistent AF underwent LA-LGE-MRI and high-definition voltage and activation mapping (2129 ± 484 sites) in sinus rhythm prior to PVI.

Variant histologies in bladder cancer: Does the centre have an impact in detection accuracy?

Objective: To compare the accuracy in detecting variant histologies (VH) at transurethral resection of bladder (TURB) and radical cystectomy (RC) specimen among tertiary referral centres, in order to investigate potential reasons of discrepancies from the pathological point of view.

Patients And Methods: Clinical and histopathological data of TURB specimen and subsequent cystectomy specimen of 3,445 RC candidate patients have been retrospectively collected from 24 tertiary referral centres between 1980 and 2021. VH considered in the analysis were pure squamous cell carcinoma, urothelial carcinoma with squamous differentiation, pure adenocarcinoma, urothelial carcinoma with glandular differentiation, micropapillary bladder cancer (BCa), neuroendocrine BCa, and other variants.

Defining the Morbidity of Robot-Assisted Radical Cystectomy with Intracorporeal Urinary Diversion: Adoption of the Comprehensive Complication Index.

The Clavien-Dindo Classification (CDC) only reports the postoperative complication of highest grade. It is thus of limited value for radical cystectomy, after which patients usually experience multiple complications. The Comprehensive Complication Index (CCI) is a novel scoring system, which incorporates all postoperative events in one single value.

An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images.

Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging melanocytic lesions due to their ambiguous morphological features. The gold standard for its diagnosis and prognosis is the analysis of skin biopsies.

A novel self-learning framework for bladder cancer grading using histopathological images.

In recent times, bladder cancer has increased significantly in terms of incidence and mortality. Currently, two subtypes are known based on tumour growth: non-muscle invasive (NMIBC) and muscle-invasive bladder cancer (MIBC). In this work, we focus on the MIBC subtype because it has the worst prognosis and can spread to adjacent organs.

Continuing acetylsalicylic acid during Robotic-Assisted Radical Cystectomy with intracorporeal urinary diversion does not increase hemorrhagic complications: results from a large multicentric cohort.

Objectives: To evaluate whether continuing the antiplatelet drug acetylsalicylic acid≤100mg (ASA) during Robotic-assisted radical cystectomy (RARC) with intracorporeal urinary diversion (ICUD) increases the risk of peri-and postoperative hemorrhagic complications and overall morbidity. Indeed, guidelines recommend interrupting antiplatelet therapy before radical cystectomy; however, RARC with ICUD is associated to reduced estimated blood loss and blood transfusions compared to its open counterpart.

Methods: Data from a multicentric European database were analyzed.

Circumpapillary OCT-focused hybrid learning for glaucoma grading using tailored prototypical neural networks.

Glaucoma is one of the leading causes of blindness worldwide and Optical Coherence Tomography (OCT) is the quintessential imaging technique for its detection. Unlike most of the state-of-the-art studies focused on glaucoma detection, in this paper, we propose, for the first time, a novel framework for glaucoma grading using raw circumpapillary B-scans. In particular, we set out a new OCT-based hybrid network which combines hand-driven and deep learning algorithms.

Supervised Domain Adaptation for Automated Semantic Segmentation of the Atrial Cavity.

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria.

Self-Learning for Weakly Supervised Gleason Grading of Local Patterns.

Prostate cancer is one of the main diseases affecting men worldwide. The gold standard for diagnosis and prognosis is the Gleason grading system. In this process, pathologists manually analyze prostate histology slides under microscope, in a high time-consuming and subjective task.

Video-Based System for Automatic Measurement of Barbell Velocity in Back Squat.

Velocity-based training is a contemporary method used by sports coaches to prescribe the optimal loading based on the velocity of movement of a load lifted. The most employed and accurate instruments to monitor velocity are linear position transducers. Alternatively, smartphone apps compute mean velocity after each execution by manual on-screen digitizing, introducing human error.

WeGleNet: A weakly-supervised convolutional neural network for the semantic segmentation of Gleason grades in prostate histology images.

Background And Objective: Prostate cancer is one of the main diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic tool for prostate cancer. This is obtained via the visual analysis of cancerous patterns in prostate biopsies performed by expert pathologists, and the aggregation of the main Gleason grades in a combined score.