Prosper Hospital

Healthcare is increasingly driven by data-intensive applications that span medical imaging, biosignal monitoring, and multilingual patient records. While cloud platforms provide scalable resources for storage and advanced analytics, latency and security concerns make it essential to integrate intelligent processing at the edge. Traditional edge-cloud healthcare pipelines face limitations in handling heterogeneous data modalities, supporting multilingual interpretation, and maintaining privacy under regulatory frameworks. To address these challenges, this paper proposes a novel multilingual Large Language Model (LLM)-enhanced framework for secure signal and image analytics in edge-cloud healthcare systems. The framework fuses multimodal data streams such as ECG signals, MRI scans, and multilingual clinical text-using LLM-based contextual reasoning to enable adaptive decision support. A security layer is embedded through federated edge training, encryption protocols, and differential privacy, ensuring compliance with HIPAA and GDPR. Experimental evaluation across public healthcare datasets demonstrates that the proposed system achieves <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$7-12 {\%}$</tex> higher diagnostic accuracy in multilingual cases compared to unimodal baselines, while reducing latency by 18% through edge-assisted inference. These results indicate that multilingual LLM integration into healthcare edge-cloud pipelines offers a resilient, secure, and globally inclusive approach for next-generation medical analytics.

The recent emergence of Large Language Models (LLMs) has progressed toward feasible use-cases of conversational agents which expand into domain-specific advanced uses in healthcare, financial services, metal fabrication, and legal services. Nevertheless, to integrate LLMs in production of such niche areas, they need a powerful operational framework, named the LLMOps, that will secure scalability, compliance, security, and performance optimization. The current paper proposes an architecture of domain-specific LLM APIs, orienting at the design modules, domain-constrained prompt engineering, knowledge-based inference architecture, and continuous fine-tuning pipelines. The framework suggested will include API orchestration layers, domain ontologies, compliance-aware data governance, along with latency, throughput, and explainability monitors, to control the demands of latency, throughput and explainability. In addition, the architecture uses hybrid deployment options that combine on-premises, cloud, and edge-based forms of LLM realizations to support the various requirements in the industry. The experimental testing of several spheres indicates a higher precision in responding as well as a diminution of the prevalence of hallucinate moments and compliance with the sector-based regulations. The results establish LLMOps-enabled APIs as an important foundation to the next generation of industry grade language interfaces, a port of call between the general-purpose LLM capabilities and enterprise-specific tasks.

Abstract This study examines the impact of online dispute resolution (ODR) on the efficiency of the Indian judiciary, focusing on an online platform used in Lok Adalats, community-based legal forums in India. The study addresses the challenges posed by India’s extensive case backlog and the additional strain caused by the COVID-19 pandemic. It employs a Randomized Control Trial (RCT) methodology to evaluate the integration of chatbots in ODR processes. The findings suggest that chatbot integration maintains resolution time while enhancing user engagement. This research highlights the potential of leveraging technology to incorporate procedural justice principles, thereby improving public trust and the effectiveness of the legal system.

This systematic review assesses whether limited-English proficiency (LEP) increases risk of having poor perioperative care and outcomes. This review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 99 articles were identified in Embase and PubMed and screened by 2 independent reviewers. Ten studies, which included 3 prospective cohort studies, 6 retrospective cohort studies, and 1 cross-sectional study, met inclusion and exclusion criteria. All studies were of high-quality rating according to the Newcastle-Ottawa scale. Subsequently, the Levels of Evidence Rating Scale for Prognostic/Risk Studies and Grade Practice Recommendations from the American Society of Plastic Surgeons were used to assess the quality of evidence of each study and the strength of the body of evidence, respectively. There is strong evidence that professional medical interpreter (PMI) use or having a language-concordant provider for LEP patients improves understanding of the procedural consent. The evidence also highly suggests that LEP patients are at risk of poorer postoperative pain control and poorer understanding of discharge instructions compared with English-speaking patients. Further studies are needed to discern whether consistent PMI use can minimize the disparities in pain control and discharge planning between LEP and English-proficient (EP) patients. There is some evidence that LEP status is not associated with differences in having adequate access to and receiving surgical preoperative evaluation. However, the evidence is weak given the small number of studies available. There are currently no studies on whether LEP status impacts access to preoperative evaluation by an anesthesiology-led team to optimize the patient for surgery. There is some evidence to suggest that LEP patients, especially when PMI services are not used consistently, are at risk for increased length of stay, more complications, and worse clinical outcomes. The available outcomes research is limited by the relative infrequency of complications. Additionally, only 4 studies validated whether LEP patients utilized a PMI. Future studies should use larger sample sizes and ascertain whether LEP patients utilized a PMI, and the effect of PMI use on outcomes.

Malignant peritoneal mesothelioma is a rare tumor entity. Although cytoreductive surgery and hyperthermic intraperitoneal chemotherapy have increased overall survival, its prognosis remains poor. Established chemotherapeutics include mitomycin C (MMC) and cisplatin (CP), both characterized by severe side effects. GP-2250 is a novel antineoplastic agent, currently under clinical investigation. This in vitro study aims to investigate effects of GP-2250 including combinations with CP and MMC on malignant mesothelioma. JL-1 and MSTO-211H mesothelioma cell lines were treated with increasing doses of GP-2250, CP, MMC and combination therapies of GP-2250 + CP/MMC. Microscopic effects were documented, and a flow-cytometric apoptosis/necrosis assay was performed. Synergistic and antagonistic effects were analyzed by computing the combination index by Chou-Talalay. GP-2250 showed an antiadhesive effect on JL-1 and MSTO-211H spheroids. It had a dose-dependent cytotoxic effect on both monolayer and spheroid cultured cells, inducing apoptosis and necrosis. Combination treatments of GP-2250 with MMC and CP led to significant reductions of the effective doses of CP/MMC. Synergistic and additive effects were observed. GP-2250 showed promising antineoplastic effects on malignant mesothelioma cells in vitro especially in combination with CP/MMC. This forms the basis for further in vivo and clinical investigations in order to broaden treatment options.

Background:Matrix-associated autologous chondrocyte implantation (ACI) is awell-established treatment for cartilage defects. High-level evidence atmidterm follow-up is limited, especially for ACI using spheroids (sphericalaggregates of ex vivo expanded human autologous chondrocytes andself-synthesized extracellular matrix).Purpose:To assess the safety and efficacy of 3-dimensional matrix-associated ACIusing spheroids to treat medium to large cartilage defects on differentlocations in the knee joint (patella, trochlea, and femoral condyle) at5-year follow-up.Study Design:Cohort study; Level of evidence, 2.Methods:A total of 75 patients aged 18 to 50 years with medium to large (4-10cm2), isolated, single cartilage defects, InternationalCartilage Repair Society grade 3 or 4, were randomized on a single-blindbasis to treatment with ACI at 1 of 3 dose levels: 3 to 7, 10 to 30, or 40to 70 spheroids/cm2 of defect size. Outcomes were assessed viachanges from baseline Knee injury and Osteoarthritis Outcome Score (KOOS),International Knee Documentation Committee score, and modified Lysholmassessments at 1- and 5-year follow-up. Structural repair was evaluatedusing MOCART (magnetic resonance observation of cartilage repair tissue)score. Treatment-related adverse events were assessed up to 5 years for allpatients. The overall KOOS at 12 months was assessed for superiority versusbaseline in a 1-sample, 2-sided t test.Results:A total of 73 patients were treated: 24 in the low-dose group, 25 in themedium-dose group, and 24 in the high-dose group. The overall KOOS improvedfrom 57.0 ± 15.2 at baseline to 73.4 ± 17.3 at 1-year follow-up(P < .0001) and 76.9 ± 19.3 at 5-year follow-up(P < .0001), independent of the applied dose. Thedifferent defect locations (patella, trochlea, and weightbearing part of thefemoral condyles; P = .2216) and defect sizes(P = .8706) showed comparable clinical improvement. Nodifferences between the various doses were observed. The overall treatmentfailure rate until 5 years was 4%. Most treatment-related adverse eventsoccurred within the first 12 months after implantation, with the mostfrequent adverse reactions being joint effusion (n = 71), arthralgia (n =14), and joint swelling (n = 9).Conclusion:ACI using spheroids was safe and effective for defect sizes up to 10cm2 and showed maintenance of efficacy up to 5 years for all3 doses that were investigated.Registration:NCT01225575 (ClinicalTrials.gov identifier); 2009-016816-20 (EudraCTnumber).

Zielsetzung Die Therapie von Patient/Innen mit Mammakarzinom wird immer subgruppenspezifischer. Das Wissen zur optimalen Therapieindikation, -Sequenz und Medikation steigt und somit wird die optimale Versorgung der Patienten für den Therapeuten komplexer. Dieser Herausforderung begegneten wir mit der Gründung des Studiennetzwerkes Rhein-Ruhr mit dem Ziel, die Studieneinschlüsse in den teilnehmenden Zentren zu verbessern, neue Medikamente im Rahmen von Studien einem größeren Patientenkollektiv anbieten zu können, sowie den edukativen Austausch zu verbessern. Die Ergebnisse dieser Kooperation sollen dargestellt werden.