Hasil untuk "Diseases of the musculoskeletal system"

Muhammad Hammad Maqsood, Mubashir Sajid, Khubaib Ahmed et al.

This research paper outlines the development and implementation of a novel Clinical Decision Support System (CDSS) that integrates AI predictive modeling with medical knowledge bases. It utilizes the quantifiable information elements in lab results for inferring likely diagnoses a patient might have. Subsequently, suggesting investigations to confirm the likely diagnoses -- an assistive tool for physicians. The system fuses knowledge contained in a rule-base expert system with inferences of data driven predictors based on the features in labs. The data for 593,055 patients was collected from 547 primary care centers across the US to model our decision support system and derive Real-Word Evidence (RWE) to make it relevant for a large demographic of patients. Our Rule-Base comprises clinically validated rules, modeling 59 health conditions that can directly confirm one or more of diseases and assign ICD-10 codes to them. The Likely Diagnosis system uses multi-class classification, covering 37 ICD-10 codes, which are grouped together into 11 categories based on the labs that physicians prescribe to confirm the diagnosis. This research offers a novel system that assists a physician by utilizing medical profile of a patient and routine lab investigations to predict a group of likely diseases and then confirm them, coupled with providing explanations for inferences, thereby assisting physicians to reduce misdiagnosis of patients in clinical decision-making.

In Ah Choi, Akio Umemoto, Masataka Mizuno et al.

Abstract Bone is constantly being remodeled, and this process is orchestrated by a dynamic crosstalk of bone cells, including osteoclasts, osteoblasts, and osteocytes. Recent evidence suggests that cellular metabolism plays a crucial role in the differentiation and function of bone cells and facilitates the adaptation of bone cells to changes in the bone microenvironment. Moreover, bone affects whole-body energy metabolism. However, it is not yet completely understood how different cells in bone coordinate metabolic processes under physiological conditions, and how altered metabolic processes in bone cells contribute to pathological conditions where the balance among bone cells is disrupted. Therefore, gaining a better understanding of the distinct metabolic requirements of bone cells can provide crucial insights into the dysfunction of bone cells in pathological conditions and can be used to identify new therapeutic approaches to treat bone diseases. Here, we discuss recent advances in understanding metabolic reprogramming in bone cells.

T. Harris, L. Launer, G. Eiriksdottir et al.

Andreas Spilz, Heiko Oppel, Michael Munz

Automated evaluation of movement quality holds significant potential for enhancing physiotherapeutic treatments and sports training by providing objective, real-time feedback. However, the effectiveness of deep learning models in assessing movements captured by inertial measurement units (IMUs) is often hampered by limited data availability, class imbalance, and label ambiguity. In this work, we present a novel data augmentation method that generates realistic IMU data using musculoskeletal simulations integrated with systematic modifications of movement trajectories. Crucially, our approach ensures biomechanical plausibility and allows for automatic, reliable labeling by combining inverse kinematic parameters with a knowledge-based evaluation strategy. Extensive evaluations demonstrate that augmented variants closely resembles real-world data, significantly improving the classification accuracy and generalization capability of neural network models. Additionally, we highlight the benefits of augmented data for patient-specific fine-tuning scenarios, particularly when only limited subject-specific training examples are available. Our findings underline the practicality and efficacy of this augmentation method in overcoming common challenges faced by deep learning applications in physiotherapeutic exercise evaluation.

Sri Varsha Mulakala, G. Neeharika, P. Vinay Kumar et al.

The recent increase in morbidity is primarily due to chronic diseases including Diabetes, Heart disease, Lung cancer, and brain tumours. The results for patients can be improved, and the financial burden on the healthcare system can be lessened, through the early detection and prevention of certain disorders. In this study, we built a machine-learning model for predicting the existence of numerous diseases utilising datasets from various sources, including Kaggle, Dataworld, and the UCI repository, that are relevant to each of the diseases we intended to predict. Following the acquisition of the datasets, we used feature engineering to extract pertinent features from the information, after which the model was trained on a training set and improved using a validation set. A test set was then used to assess the correctness of the final model. We provide an easy-to-use interface where users may enter the parameters for the selected ailment. Once the right model has been run, it will indicate whether the user has a certain ailment and offer suggestions for how to treat or prevent it.

Gatam AR, Gatam L, Ajiantoro A et al.

Asrafi Rizki Gatam,1– 3 Luthfi Gatam,1– 3 Ajiantoro Ajiantoro,3 Omar Luthfi,3 Phedy Phedy,1,2 Harmantya Mahadhipta,1 Syafrudin Husin,1 Ilham Suryo Wibowo Antono,4 Erwin Ardian Noor,2 Karina Sylvana Gani,1 Mitchel Mitchel,1 Erica Kholinne1,5 1Department of Orthopedic and Traumatology, Gatam Institute Eka Hospital, Jakarta, Indonesia; 2Department of Orthopedic and Traumatology department, Fatmawati Hospital, Jakarta, Indonesia; 3Department of Orthopedic and Traumatology Department, Premier Bintaro Hospital, Jakarta, Indonesia; 4Orthopaedi dan Traumatologi Department, Faculty of Medicine Universitas Indonesia– Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia; 5Department of Surgery, Faculty of Medicine, Universitas Trisakti, Jakarta, IndonesiaCorrespondence: Erica Kholinne, Department of Surgery, Faculty of Medicine, Universitas Trisakti, Jakarta, Indonesia, Tel +628118682265, Email erica@trisakti.ac.idIntroduction: Facet cysts are degenerative lesions near the facet joints, often seen in older adults with lumbar or radicular pain. They can compress nerves and cause significant morbidity. Treatment options range from conservative care to surgery. This article outlines the Biportal Endoscopic Spine Surgery (BESS) technique using interlaminar ipsilateral or contralateral approaches for symptom relief.Methods: This paper outlines the surgical techniques of Biportal Endoscopic Spine Surgery (BESS), utilizing both ipsilateral and contralateral interlaminar approaches. The choice of approach was determined by the location and characteristics of the synovial cyst. It details the surgical process, including portal placement, visualization, trajectory differences between approaches, and steps for cyst removal.Results: Biportal endoscopic spine surgery is a safe and effective minimally invasive treatment for symptomatic lumbar facet cysts, especially in elderly patients. The contralateral approach offers better visualization, improved dural dissection, and greater facet joint preservation, making it ideal for medial or adherent cysts. It also reduces nerve root manipulation and postoperative instability. In contrast, the ipsilateral approach is more suitable for lateral cysts.Conclusion: The choice between contralateral and ipsilateral approaches in biportal endoscopic facet cyst removal depends on cyst location and anatomical considerations. The contralateral approach is better suited for medial or adherent cysts, offering improved access with less facet disruption. Meanwhile, the ipsilateral approach provides a direct path for lateral cysts but may require more nerve manipulation and facet joint resection. A personalized surgical strategy is essential to optimize access, ensure nerve safety, and maintain spinal stability.Keywords: biportal endoscopic, contralateral, ipsilateral, interlaminar approach, facet cyst, lumbar

Qingyang Huang, Lang Xiao, Shuaikang Wang et al.

Abstract Purpose The poor prognosis of adult patients with spinal deformity following long-segment spinal fusion surgery remains a major concern. Our study aims to investigate the impact of an Enhanced Recovery After Surgery (ERAS) protocol on the prognosis of adult patients with spinal deformity. Methods This study focused on a retrospective review of a database of previous adult spinal deformity. Adult patients with spinal deformity who underwent long-segment fusion surgery from July 2016 to July 2022 were evaluated, from July 2016 to July 2019 for the pre-ERAS patient group and from July 2019 to July 2022 for the ERAS group. Demographic data, radiological sagittal parameters, and intraoperative data were collected from all patients. The length of hospital stay, postoperative complications, and 90-day readmission rates were compared between the two groups. Additionally, multivariate regression models were used to analyze the predictors of postoperative length of stay, postoperative complications, and 90-day readmission rates. Results A total of 215 patients were included in this study, 102 patients in the pre-ERAS group and 113 patients in the ERAS group. Postoperative outcomes in the ERAS group included significantly lower postoperative length of stay (LOS) (13.09 ± 4.57 vs. 11.13 ± 4.16, P = 0.001); significantly lower rate of postoperative complications (52.0% vs. 29.2%, P < 0.001) and significantly lower 90-day readmission rates (14.7% vs. 6.19%, P = 0.040). Multivariate linear regression showed that fewer ERAS (P = 0.022), later drain placement (P = 0.027), and more complications (P = 0.002) were significantly associated with longer postoperative LOS. Multivariate logistic regression showed that fewer ERAS (P = 0.015) and later drain removal (P = 0.041) were significantly associated with more complications, and more ERAS (P = 0.009), earlier postoperative LOS (P = 0.020), and earlier urinary catheter removal (P = 0.034) were significantly associated with the 90-day readmission rates. Conclusions According to the results of our study, it is necessary to implement an ERAS protocol for adult patients with spinal deformity undergoing long-segment fusion surgery. The ERAS protocol is effective in reducing postoperative hospital length of stay, incidence of surgical complications, and 90-day readmission rates.

Weiye Fan, Bei Jia, Jianchao Chen et al.

Abstract Background PMMA bone cement is known to induce tissue inflammation around implants. A previous research group developed a novel material, enoxaparin sodium bone cement (ES-PMMA), which combines 40 g of PMMA bone cement with 8000 AxaIU of enoxaparin sodium. This innovative bone cement has demonstrated anti-inflammatory and immunomodulatory properties within the local tissue microenvironment. This study aimed to explore the underlying molecular mechanisms. Methods RAW264.7 cells were treated with different bone cement extract mediums to observe macrophage polarization and the expression of inflammatory factors. RAW264.7 cells treated with different bone cement extract mediums were collected for lncRNA sequencing, and the sequencing results were analyzed using bioinformatics. The lncRNA NONMMUT104330.1-miR-709-DDX58 regulatory axis was constructed based on the competing endogenous RNA mechanism. Subsequently, lncRNA NONMMUT104330.1 in RAW264.7 cells was either knocked down or overexpressed to observe the inflammatory response of the cells. Results ES-PMMA bone cement induces M2 polarization of macrophages and increases the expression of anti-inflammatory factors. A bioinformatics analysis was conducted on the sequencing results to construct the lncRNA NONMMUT104330.1-miR-709-DDX58 regulatory axis. A dual-luciferase reporter gene assay was employed to verify the binding feasibility of the axis, and the results demonstrated that miR-709 could bind to the molecular sites of lncRNA NONMMUT104330.1 and DDX58, respectively. Knockout and overexpression experiments of lncRNA NONMMUT104330.1 demonstrated that the knockdown of lncRNA NONMMUT104330.1 induced M2 polarization in RAW264.7 cells, leading to a reduction in pro-inflammatory factor expression and an increase in anti-inflammatory factor expression. Conversely, upon overexpression of lncRNA NONMMUT104330.1, RAW264.7 cells were polarized to M1, resulting in elevated levels of pro-inflammatory factors. Conclusion Enoxaparin sodium bone cement can induce M2 polarization of macrophages, thereby playing an anti-inflammatory immunomodulatory role. The lncRNA NONMMUT104330.1-miR-709-DDX58 axis may significantly contribute to this process. Clinical trial number Not applicable.

Nadeem Akhtar Qureshi, Ravi Prakash Futela

Introduction: Neonatal Obstetric fractures are rare birth injuries that newborns sustained from trauma during delivery and birth process. Long bone fractures are common in vaginal breech deliveries. A cesarean section is considered a relatively safe and preferred mode of delivery of breech fetuses to prevent birth trauma and decrease the risk of fetal head entrapment; nevertheless, it can lead to femur fracture in newborn rarely. Case Report: A 3915 g male child born at 38 weeks and 4 days of gestation to a primigravida aged 31 years by emergency Lower Segment Cesarean Section for Premature Rupture of Membrane with breech presentation. During extraction, the newborn sustained a fracture to his right femur shaft. X-rays confirmed the diagnosis. The fracture was treated successfully with a toe-groin cast for 25 days with complete healing. Conclusion: As compared to vaginal breech delivery, cesarean section reduces the risk of traumatic birth injuries; however, it does not completely eliminate the possibility of birth injuries and long bone fractures in newborns. Orthopedic opinion must be sought, if the obstetrician and neonatologist suspect any birth trauma in difficult deliveries. Immobilization of the limb leads to complete healing of the fracture without any sequel.

J. Pépin, S. Bailly, P. Rinder et al.

The nationwide claims data lake for sleep apnoea (ALASKA)—real-life data for understanding and increasing obstructive sleep apnea (OSA) quality of care study—investigated long-term continuous positive airway pressure (CPAP) termination rates, focusing on the contribution of comorbidities. The French national health insurance reimbursement system data for new CPAP users aged ≥18 years were analyzed. Innovative algorithms were used to determine the presence of specific comorbidities (hypertension, diabetes and chronic obstructive pulmonary disease (COPD)). Therapy termination was defined as cessation of CPAP reimbursements. A total of 480,000 patients were included (mean age 59.3 ± 13.6 years, 65.4% male). An amount of 50.7, 24.4 and 4.3% of patients, respectively, had hypertension, diabetes and COPD. Overall CPAP termination rates after 1, 2 and 3 years were 23.1, 37.1 and 47.7%, respectively. On multivariable analysis, age categories, female sex (1.09 (1.08–1.10) and COPD (1.12 (1.10–1.13)) and diabetes (1.18 (1.16–1.19)) were significantly associated with higher CPAP termination risk; patients with hypertension were more likely to continue using CPAP (hazard ratio 0.96 (95% confidence interval 0.95–0.97)). Therapy termination rates were highest in younger or older patients with ≥1 comorbidity. Comorbidities have an important influence on long-term CPAP continuation in patients with OSA.

Renpeng Zhou, Weirong Hu, Peter X. Ma et al.

AbstractBone and joint-related diseases, including osteoarthritis (OA), rheumatoid arthritis (RA), and bone tumors, pose significant health challenges due to their debilitating effects on the musculoskeletal system. 14-3-3 proteins, a family of conserved regulatory molecules, play a critical role in the pathology of these diseases. This review discusses the intricate structure and multifunctionality of 14-3-3 proteins, their regulation of signaling pathways, and their interactions with other proteins. We underscore the significance of 14-3-3 proteins in the regulation of osteoblasts, osteoclasts, chondrocytes, and bone remodeling, all key factors in the maintenance and dysfunction of bone and joint systems. Specific focus is directed toward elucidating the contribution of 14-3-3 proteins in the pathology of OA, RA, and bone malignancies, where dysregulated 14-3-3-mediated signaling cascades have been implicated in the disease processes. This review illuminates how the perturbation of 14-3-3 protein interactions can lead to the pathological manifestations observed in these disorders, including joint destruction and osteolytic activity. We highlight cutting-edge research that positions 14-3-3 proteins as potential biomarkers for disease progression and as innovative therapeutic targets, offering new avenues for disease intervention and management.

Jacquelyn Nestor, Hyon Choi, Christian Mancini et al.

ObjectiveWe sought to determine the impact of hydroxychloroquine (HCQ) dose on the risk of hospitalizations for systemic lupus erythematosus (SLE).MethodsWe conducted a case‐crossover study within an academic health system, including patients with SLE who used HCQ and had ≥1 hospitalization for active SLE between January 2011 and December 2021. Case periods ended in hospitalization for SLE, whereas control periods did not. The exposures were the average weight‐based HCQ dose, categorized as ≤5 or >5 mg/kg/day, and non–weight‐based HCQ dose, categorized as <400 or 400 mg/day, assessed during each six‐month case or control period. Odds ratios (ORs) were calculated using conditional logistic regression and adjusted for prior disease activity, kidney function, glucocorticoid use, and other immunosuppressant use.ResultsOf 2,974 patients with SLE who used HCQ (mean age 36.5 years; 92% female), 584 had ≥1 hospitalization with primary discharge diagnosis of SLE. Of these, 122 had ≥1 hospitalization for active SLE while using HCQ and had ≥1 control period with HCQ use during the study period. Lower HCQ weight‐based dose (≤5 vs >5 mg/kg/day) and non–weight‐based dose (<400 vs 400 mg/day) were each associated with increased hospitalizations for active SLE (adjusted OR 4.20, 95% confidence interval [CI] 1.45–12.19, and adjusted OR 3.39, 95% CI 1.31–8.81).ConclusionThe use of lower doses of HCQ was associated with an increased risk of hospitalizations for active SLE. Although the long‐term risk of HCQ retinopathy must be acknowledged, this must be balanced with the short‐term and cumulative risks of increased SLE activity.image

Cécile Trottet, Manuel Schürch, Ahmed Allam et al.

We propose a deep generative approach using latent temporal processes for modeling and holistically analyzing complex disease trajectories, with a particular focus on Systemic Sclerosis (SSc). We aim to learn temporal latent representations of the underlying generative process that explain the observed patient disease trajectories in an interpretable and comprehensive way. To enhance the interpretability of these latent temporal processes, we develop a semi-supervised approach for disentangling the latent space using established medical knowledge. By combining the generative approach with medical definitions of different characteristics of SSc, we facilitate the discovery of new aspects of the disease. We show that the learned temporal latent processes can be utilized for further data analysis and clinical hypothesis testing, including finding similar patients and clustering SSc patient trajectories into novel sub-types. Moreover, our method enables personalized online monitoring and prediction of multivariate time series with uncertainty quantification.

Bryan J. Ranger, Kevin M. Moerman, Micha Feigin et al.

Given its real-time capability to quantify mechanical tissue properties, ultrasound shear wave elastography holds significant promise in clinical musculoskeletal imaging. However, existing shear wave elastography methods fall short in enabling full-limb analysis of 3D anatomical structures under diverse loading conditions, and may introduce measurement bias due to sonographer-applied force on the transducer. These limitations pose numerous challenges, particularly for 3D computational biomechanical tissue modeling in areas like prosthetic socket design. In this feasibility study, a clinical linear ultrasound transducer system with integrated shear wave elastography capabilities was utilized to scan both a calibrated phantom and human limbs in a water tank imaging setup. By conducting 2D and 3D scans under varying compressive loads, this study demonstrates the feasibility of volumetric ultrasound shear wave elastography of human limbs. Our preliminary results showcase a potential method for evaluating 3D spatially varying tissue properties, offering future extensions to computational biomechanical modeling of tissue for various clinical scenarios.

Jixun Yao, Nikita Kuzmin, Qing Wang et al.

Speaker anonymization is an effective privacy protection solution that conceals the speaker's identity while preserving the linguistic content and paralinguistic information of the original speech. To establish a fair benchmark and facilitate comparison of speaker anonymization systems, the VoicePrivacy Challenge (VPC) was held in 2020 and 2022, with a new edition planned for 2024. In this paper, we describe our proposed speaker anonymization system for VPC 2024. Our system employs a disentangled neural codec architecture and a serial disentanglement strategy to gradually disentangle the global speaker identity and time-variant linguistic content and paralinguistic information. We introduce multiple distillation methods to disentangle linguistic content, speaker identity, and emotion. These methods include semantic distillation, supervised speaker distillation, and frame-level emotion distillation. Based on these distillations, we anonymize the original speaker identity using a weighted sum of a set of candidate speaker identities and a randomly generated speaker identity. Our system achieves the best trade-off of privacy protection and emotion preservation in VPC 2024.

Nikolai Ramadanov, Mikhail Salzmann, Maximilian Voss et al.

Jonatan C. S. de Carvalho, P. V. da Silva-Neto, D. M. Toro et al.

COVID-19 is associated with a dysregulated immune response. Currently, several medicines are licensed for the treatment of this disease. Due to their significant role in inhibiting pro-inflammatory cytokines and lipid mediators, glucocorticoids (GCs) have attracted a great deal of attention. Similarly, the endocannabinoid (eCB) system regulates various physiological processes including the immunological response. Additionally, during inflammatory and thrombotic processes, phospholipids from cell membranes are cleaved to produce platelet-activating factor (PAF), another lipid mediator. Nonetheless, the effect of GCs on this lipid pathway during COVID-19 therapy is still unknown. This is a cross-sectional study involving COVID-19 patients (n = 200) and healthy controls (n = 35). Target tandem mass spectrometry of plasma lipid mediators demonstrated that COVID-19 severity affected eCBs and PAF synthesis. This increased synthesis of eCB was adversely linked with systemic inflammatory markers IL-6 and sTREM-1 levels and neutrophil counts. The use of GCs altered these lipid pathways by reducing PAF and increasing 2-AG production. Corroborating this, transcriptome analysis of GC-treated patients blood leukocytes showed differential modulation of monoacylglycerol lipase and phospholipase A2 gene expression. Altogether, these findings offer a breakthrough in our understanding of COVID-19 pathophysiology, indicating that GCs may promote additional protective pharmacological effects by influencing the eCB and PAF pathways involved in the disease course.

A. Bahadori, B. Kuhlmann, D. Debray et al.

Background: Congenital portosystemic shunts (CPSS) are rare vascular anomalies resulting in communications between the portal venous system and the systemic venous circulation, affecting an estimated 30,000 to 50,000 live births. CPSS can present at any age as a multi-system disease of variable severity mimicking both common and rare pediatric conditions. Case presentations: Case A: A vascular malformation was identified in the liver of a 10-year-old girl with tall stature, advanced somatic maturation, insulin resistance with hyperinsulinemia, hyperandrogenemia and transient hematuria. Work-up also suggested elevated pulmonary pressures. Case B: A young girl with trisomy 8 mosaicism with a history of neonatal hypoglycemia, transient neonatal cholestasis and tall stature presented newly increased aminotransferase levels at 6 years of age. Case C: A 3-year-old boy with speech delay, tall stature and abdominal pain underwent abdominal ultrasound (US) showing multiple liver nodules, diagnosed as liver hemangiomas by hepatic magnetic resonance imaging (MRI). Management and outcome: After identification of a venous malformation on liver Doppler US, all three patients were referred to a specialized liver center for further work-up within 12 to 18 months from diagnosis. Angio-computed tomography (CT) scan confirmed the presence of either an intrahepatic or extrahepatic CPSS with multiples liver nodules. All three had a hyperintense signal in the globus pallidus on T1 weighted cerebral MRI. Right heart catheterization confirmed pulmonary hypertension in cases A and C. Shunts were closed either using an endovascular or surgical approach. Liver nodules were either surgically removed if there was a risk of malignant degeneration or closely monitored by serial imaging when benign. Conclusion: These cases illustrate most of the common chief complaints and manifestations of CPSS. Liver Doppler US is the key to diagnosis. Considering portosystemic shunts in the diagnostic work-up of a patient with unexplained endocrine, liver, gastro-intestinal, cardiovascular, hematological, renal or neurocognitive disorder is important as prompt referral to a specialized center may significantly impact patient outcome.

Wentao Zhang, Yujun Huang, Tong Zhang et al.

Currently intelligent diagnosis systems lack the ability of continually learning to diagnose new diseases once deployed, under the condition of preserving old disease knowledge. In particular, updating an intelligent diagnosis system with training data of new diseases would cause catastrophic forgetting of old disease knowledge. To address the catastrophic forgetting issue, an Adapter-based Continual Learning framework called ACL is proposed to help effectively learn a set of new diseases at each round (or task) of continual learning, without changing the shared feature extractor. The learnable lightweight task-specific adapter(s) can be flexibly designed (e.g., two convolutional layers) and then added to the pretrained and fixed feature extractor. Together with a specially designed task-specific head which absorbs all previously learned old diseases as a single "out-of-distribution" category, task-specific adapter(s) can help the pretrained feature extractor more effectively extract discriminative features between diseases. In addition, a simple yet effective fine-tuning is applied to collaboratively fine-tune multiple task-specific heads such that outputs from different heads are comparable and consequently the appropriate classifier head can be more accurately selected during model inference. Extensive empirical evaluations on three image datasets demonstrate the superior performance of ACL in continual learning of new diseases. The source code is available at https://github.com/GiantJun/CL_Pytorch.

Haider Sultan, Hafiza Farwa Mahmood, Noor Fatima et al.

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.