Tuning the reactivity of TiO_(2)layer with uniform distribution of Sub-5 nm Fe_(2)O_(3)particles via in situ voltage-assisted oxidation for robust catalytic reduction

The trade-off between efficiency and stability has limited the application of TiO_(2)as a catalyst due to its poor surface reactivity.Here,we present a modification of a TiO_(2)layer with highly stable Sub-5 nm Fe_(2)O_(3)nanoparticles(NP)by modulating its structure-surface reactivity relationship to attain efficiency-stability balance via a voltage-assisted oxidation approach.In situ simultaneous oxidation of the Ti substrate and Fe precursor using high-energy plasma driven by high voltage resulted in uniform distribution of Fe_(2)O_(3)NP embedded within porous TiO_(2)layer.Comprehensive surface characterizations with density functional theory demonstrated an improved electronic transition in TiO_(2)due to the presence of surface defects from reactive oxygen species and possible charge transfer from Ti to Fe;it also unexpectedly increased the active site in the TiO_(2)layer due to uncoordinated electrons in Sub-5 nm Fe_(2)O_(3)NP/TiO_(2)catalyst,thereby enhancing the adsorption of chemical functional groups on the catalyst.This unique embedded structure exhibited remarkable improvement in reducing 4-nitrophenol to 4-aminophenol,achieving approximately 99%efficiency in 20 min without stability decay after 20 consecutive cycles,outperforming previously reported TiO_(2)-based catalysts.This finding proposes a modified-electrochemical strategy enabling facile construction of TiO_(2)with nanoscale oxides extandable to other metal oxide systems.

Surface engineering of ZnO electrocatalyst by N doping towards electrochemical CO_(2) reduction

The discovery of efficient,selective,and stable electrocatalysts can be a key point to produce the largescale chemical fuels via electrochemical CO_(2) reduction(ECR).In this study,an earth-abundant and nontoxic ZnO-based electrocatalyst was developed for use in gas-diffusion electrodes(GDE),and the effect of nitrogen(N)doping on the ECR activity of ZnO electrocatalysts was investigated.Initially,a ZnO nanosheet was prepared via the hydrothermal method,and nitridation was performed at different times to control the N-doping content.With an increase in the N-doping content,the morphological properties of the nanosheet changed significantly,namely,the 2D nanosheets transformed into irregularly shaped nanoparticles.Furthermore,the ECR performance of Zn O electrocatalysts with different N-doping content was assessed in 1.0 M KHCO_(3) electrolyte using a gas-diffusion electrode-based ECR cell.While the ECR activity increased after a small amount of N doping,it decreased for higher N doping content.Among them,the N:ZnO-1 h electrocatalysts showed the best CO selectivity,with a faradaic efficiency(FE_(CO))of 92.7%at-0.73 V vs.reversible hydrogen electrode(RHE),which was greater than that of an undoped Zn O electrocatalyst(FE_(CO)of 63.4%at-0.78 V_(RHE)).Also,the N:ZnO-1 h electrocatalyst exhibited outstanding durability for 16 h,with a partial current density of-92.1 mA cm^(-2).This improvement of N:ZnO-1 h electrocatalyst can be explained by density functional theory calculations,demonstrating that this improvement of N:ZnO-1 h electrocatalyst comes from(ⅰ)the optimized active sites lowering the free energy barrier for the rate-determining step(RDS),and(ⅱ)the modification of electronic structure enhancing the electron transfer rate by N doping.

In-depth analysis of VARTM-based solid-state supercapacitors utilizing CNT-dispersed cobalt-bismuth-samarium ternary hydroxide on woven carbon fiber for enhanced energy storage

Multi-metal hydroxides possess unique physical and chemical properties,making them promising candidates for supercapacitor working electrodes.Enhancing their electrochemical performance can be achieved through a combination with carbon materials.In this study,we synthesized a composite material by hydrothermally dispersed 4,6,and 10 wt%carbon nanotubes(CNT)into ternary cobaltbismuth-samarium hydroxide(CoBiSm-TOH).These nanocomposites were employed as the material for the working electrode in a supercapacitor.The findings reveal that at 1.5 A/g,the specific capacitance of CNT3@CoBiSm-TOH,using a three-electrode system,was found to be 852.91 F/g,higher than that of CoBi-BOH,CoBiSm-TOH,CNT1@CoBiSm-TOH and CNT5@CoBiSm-TOH-measuring 699.69,750.34,789.54 and 817.79 F/g,respectively.Moreover,CNT3@CoBiSm-TOH electrodes exhibited a capacitance retention of around 88%over 10,000 cycles.To demonstrate practical applicability,CNT3@CoBiSm-TOH was grown on woven carbon fiber(WCF),and a solid-state supercapacitor device was developed using the VARTM(vacuum-assisted resin transfer molding).This device displayed a specific capacitance of 272.67 F/g at 2.25 A/g.Notably,it achieved a maximum energy density of 53.01 Wh/kg at a power density of 750 W/kg and sustained excellent cycle stability over 50,000 cycles,maintaining 70%of its initial capacitance.These results underscore the importance of interfacial nanoengineering and provide crucial insights for the development of future energy storage devices.

Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

Extracellular vesicles for neural regeneration after spinal cord injury

What is spinal cord injury:Spinal cord injury(SCI)is the damage to the structure of the bundles of cells and nerves that communicate signals from the brain to the body and extremities.The pathology of SCI includes both primary and secondary injuries(Morales et al.,2016).Physical forces such as compression,shearing,contusion,and tearing are major causes of primary injury in SCI.There are two main processes in primary injury:acute and subacute.The acute phase includes traumatic disruption of axons and hemorrhage of the blood vessels around the spinal cord.Hemorrhagic injury to the vessels can lead to increased edema within the neural and cord tissues,susceptibility to infiltration by microglia and astrocytes,excitotoxicity,and demyelination.Similarly,disruption of the blood-spinal cord barrier results in the release of inflammatory cytokines from specific cells and vessels.

Primary Ewing sarcoma of the kidney mimicking cystic papillary renal cell carcinoma in an older patient:A case repor

BACKGROUND Ewing’s sarcoma(ES)is a neuroectodermal tumor that typically occurs in the bones and soft tissues of children and young adults.Primary renal ES is rare;only a few cases and a small case series have been documented,and only four cases involved primary renal ES in older people(>65 years old).CASE SUMMARY Herein,we describe the radiological and pathological features of primary renal ES in an older person.A 76-year-old man complained of poor oral intake and was found to have a large cystic renal mass with indistinct margins on computed tomography.Ultrasound-guided biopsy revealed that the tumor contained small round blue cells.The patient underwent a right radical nephrectomy.The tumor cells showed diffuse membranous CD99,and nuclear friend leukemia integration 1 transcription factor and NK2 Homeobox 2.Fluorescence in situ hybridization revealed EWSR1 translocation.Postoperatively,18F-fluorodeoxyglucose positron emission tomography revealed no evidence of metastasis.The patient was diagnosed with primary renal ES.Six months following the surgery,local recurrence and distant metastasis were observed.Primary renal ES is rare and often lethal in older individuals.The specific imaging findings are unknown,and treatment protocols have not been standardized.CONCLUSION This case report describes the radiological and pathological features of primary renal ES in an older person.

Self-adhesive pads in defi brillation or cardioversion: risks due to unfamiliarity and recommendations

During cardiopulmonary resuscitation(CPR),defibrillation,or cardioversion,the use of self-adhesive pads instead of conventional paddles has gradually become common.In particular,it was recommended during the COVID-19 pandemic,as it allows defibrillation or cardioversion to be performed without close contact between the rescuer and patient.[1,2]Self-adhesive pads can minimize the downtime of chest compressions before and after defibrillation and protect the patient from electric arc formation,skin burns,and fi re.Once the pads are attached,electrocardiographic rhythm analysis,defibrillation,synchronous cardioversion,and cardiovascular support are all possible.Unlike paddles,self-adhesive pads can save time because the application of conductive jelly,repeated positioning,and application of 10-12 kg of pressure on the chest are not needed.The European Resuscitation Council(ERC)Guidelines 2021 state that the use of self-adhesive pads is recommended in advanced cardiovascular life support(ACLS).[3]Nevertheless,some medical staff still tend to prefer the use of conventional paddles instead of self-adhesive pads in hospitals.

Review on inorganic and polymeric materials-coordinated metal-organic-framework photocatalysts for green hydrogen evolution

Metal-organic frameworks(MOFs)possess a distinct advantage over conventional heterogeneous photocatalysts because of their carefully defined architecture and particular pores,which facilitate the targeted incorporation of other efficient cocatalysts or semiconductor materials.The integration of MOFs with other materials has resulted in significant breakthroughs,as the coupled materials improve the performance due to the combined effect.The unique MOF structures allow them to host foreign materials,which results in harvesting the visible region of the solar spectrum and effectively mitigating charge recombination by promoting charge separation.The review presents an evaluation of the latest developments in the utilization of surface and/or pore chemistry of MOF-supported heterojunctions for photocatalytic green-hydrogen generation with a basic understanding of the mechanism involved.The review begins with the basic principles of photocatalysis,the significance of MOFs,their optical properties,the methods used for synthesizing MOFs,and their coordination with other inorganic and polymeric materials.Furthermore,methods to increase photocatalytic H2 evolution using MOF-supported heterojunction have been proposed as standard practice.Lastly,to address environmental challenges,we highlight the future potential of MOF-supported heterojunctions for use in green-energy production.We hope that this review provides guidance to researchers in the development of effective heterojunctions based on MOFs to address challenges in energy applications and catalytic processes.

Chronic venous insufficiency, could it be one of the missing pieces in the puzzle of treating pain?

Pain is a common complaint among patients seeking medical care.If left un-treated,pain can become chronic,significantly affecting patients’quality of life.An accurate diagnosis of the underlying cause of pain is crucial for effective treatment.Chronic venous insufficiency(CVI)is frequently overlooked by pain physicians.Moreover,many pain physicians lack sufficient knowledge about CVI.CVI is a common condition resulting from malfunctioning or damaged valves in lower limb veins.Symptoms of CVI,ranging from mild to severe,include pain,heaviness,fatigue,itching,swelling,skin color changes,and ulcers in the lower limbs.Recently,it has become more widely known that these symptoms can be attributed to CVI.Even slight or mild CVI can cause related symptoms.Pain physicians primarily consider neuromusculoskeletal disorders when assessing patients with leg pain,and often neglect the possibility of CVI.In clinical practice,when pain physicians encounter patients with unresolved leg pain,they must assess whether the patients exhibit symptoms of CVI and conduct tests to differ-entiate CVI from other potential causes.

Use of artificial intelligence in the field of pain medicine

In this editorial we comment on the article“Potential and limitations of ChatGPT and generative artificial intelligence in medial safety education”published in the recent issue of the World Journal of Clinical Cases.This article described the usefulness of artificial intelligence(AI)in medial safety education.Herein,we focus specifically on the use of AI in the field of pain medicine.AI technology has emerged as a powerful tool,and is expected to play an important role in the healthcare sector and significantly contribute to pain medicine as further developments are made.AI may have several applications in pain medicine.First,AI can assist in selecting testing methods to identify causes of pain and improve diagnostic accuracy.Entry of a patient’s symptoms into the algorithm can prompt it to suggest necessary tests and possible diagnoses.Based on the latest medical information and recent research results,AI can support doctors in making accurate diagnoses and setting up an effective treatment plan.Second,AI assists in interpreting medical images.For neural and musculoskeletal disorders,imaging tests are of vital importance.AI can analyze a variety of imaging data,including that from radiography,computed tomography,and magnetic resonance imaging,to identify specific patterns,allowing quick and accurate image interpretation.Third,AI can predict the outcomes of pain treatments,contributing to setting up the optimal treatment plan.By predicting individual patient responses to treatment,AI algorithms can assist doctors in establishing a treatment plan tailored to each patient,further enhancing treatment effectiveness.For efficient utilization of AI in the pain medicine field,it is crucial to enhance the accuracy of AI decision-making by using more medical data,while issues related to the protection of patient personal information and responsibility for AI decisions will have to be addressed.In the future,AI technology is expected to be innovatively applied in the field of pain medicine.The advancement of AI is anticipated to have a positive impact on the entire medical field by providing patients with accurate and effective medical services.

Management of lymphedema is really a matter in patients with breast cancer

Lymphedema is a prevalent complication affecting patients with breast cancer,greatly impacting their quality of life.This editorial describes diagnostic methods and therapeutic interventions for managing lymphedema in patients with breast cancer.Diagnosis relies on clinical evaluation and objective measures,including arm circumference and volumetric assessments,along with lymphoscintigraphy and ultrasonic measurements.Treatment primarily involves complex decongestive physical therapy,comprising manual lymphatic drainage,compression therapy,exercise,and meticulous skin care.These interventions aim to reduce swelling,alleviate discomfort,and prevent further complications.Additionally,lifestyle modifications such as avoiding extreme temperatures and maintaining proper hygiene are essential.Flavonoids can be used for drug therapy.Despite its prevalence,lymphedema often receives inadequate attention in clinical practice,emphasizing the importance of raising awareness and enhancing medical services for affected individuals.Clinicians play a pivotal role in educating patients about preventive measures and ensuring timely intervention.Overall,a comprehensive approach encompassing early diagnosis,multidisciplinary management,and patient education is essential to mitigate the burden of lymphedema in patients with breast cancer and improve their overall well-being.

Solar Driven 15.7% Hydrogen Conversion by Harmony of Light Harvesting,Electron Transporting Bridge,and S-Defection in a Self-Assembled Microscale CuS/rGO/CP Photoanode

CuS is an encouraging photoelectrode candidate that meets the essential requirements for efficient solar-to-hydrogen production,but it has not been thoroughly studied.A CuS light absorber layer is grown by the self-assembly of copper and sulfur precursors on a carbon paper(CP)electrode.Simultaneously,rGO is introduced as a buffer layer to control the optical and electrical properties of the absorber.The well-ordered microstructural arrangement suppresses the recombination loss of electrons and holes owing to enhanced charge-carrier generation,separation,and transport.The potential reaching 10 mA cm^(-2)in 1.0 M KOH solution is significantly lowered to 0.87 V,and the photocurrent density at 1.23 V is 94.7 mA cm^(-2).The computational result reveals that the potential-determining step is sensitive to O^(*)stability;the lower stability of O^(*)in the thin layer of CuS/rGO decreases the free-energy gap between the initial and final states of the potential-determining step,resulting in a lowering of the onset potential.The faradaic efficiency for the photoelectrochemical oxygen evolution reaction in the optimized 2CuS/1rGO/CP photoanode is 98.60%,and the applied bias photon-to-current and the solar-to-hydrogen efficiencies are 11.2%and 15.7%,respectively,and its ultra-high performance is maintained for 250 h.These record-breaking achievement indices may be a trigger for establishing a green hydrogen economy.

Well-defined high entropy-metal nanoparticles:Detection of the multi-element particles by deep learning

Characterizing and control the chemical compositions of multi-element particles as single metal nanoparticles(mNPs) on the surfaces of catalytic metal oxide supports is challenging.This can be attributed to the heterogeneity and large size at the nanoscale,the poorly defined catalyst nanostructure,and thermodynamic immiscibility of the strongly repelling metallic elements.To address these challenges,an ultrasonic-assisted coincident electro-oxidation-reduction-precipitation(U-SEO-P) is presented to fabricate ultra-stable PtRuAgCoCuP NPs,which produces numerous active intermediates and induces strong metal-support interactions.To sort the active high-entropy mNPs,individual NPs are described on the support surface and the role of deep learning in understanding/predicting the features of PtRuAgCoCu@TiO_(x) catalysts is explained.Notably,this deep learning approach required minimal to no human input.The as-prepared PtRuAgCoCu@TiO_(x) catalysts can be used to catalyze various important chemical reactions,such as a high reduction conversion(100% in 30 s),with no loss of catalytic activity even after 20 cycles of nitroarene and ketone/aldehyde,which is several times higher than commercial Pt@TiO_(x) owing to individual PtRuAgCoCuP NPs on TiO_(x) surface.In this study,we present the "Totally Defined Catalysis" concept,which has enormous potential for the advancement of high-activity catalysts in the reduction of organic compounds.

In-situ construction of grass-like hybrid architecture responsible for extraordinary corrosion performance: Experimental and theoretical approach

Despite the engineering potential by the co-existence of inorganic and organic substances to protect vulnerable metallic materials from corrosive environments,both their interaction and in-situ formation mechanism to induce the nature-inspired composite remained less understood.The present work used three distinctive mercaptobenzazole(MB)compounds working as corrosion inhibitors,such as 2-mercaptobenzoxazole(MBO),2-mercaptobenzothiazole(MBT),and 2-mercaptobenzimidazole(MBI)in a bid to understand how the geometrical structure arising from O,S,and N atoms affected the interaction toward inorganic layer.MB compounds that were used here to control the corrosion kinetics would be interacted readily with the pre-existing MgO layer fabricated by plasma electrolysis.This phenomenon triggered the nucleation of the root network since MB compounds were seen to be adsorbed actively on the defective surface through the active sites in MB compound.Then,the molecule with twin donor atoms adjacent to the mercapto-sites affected the facile growth of the grass-like structures with‘uniform’distribution via molecular self-assembly,which showed better corrosion performance than those with having dissimilar donor atoms with the inhibition efficiency(η)of 97%approximately.The formation mechanism underlying nucleation and growth behavior of MB molecule was discussed concerning the theoretical calculation of density functional theory.

AI-Driven Energy Optimization in UAV-Assisted Routing for Enhanced Wireless Sensor Networks Performance

In recent advancements within wireless sensor networks(WSN),the deployment of unmanned aerial vehicles(UAVs)has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network functionality.This research introduces a sophisticated framework,driven by computational intelligence,that merges clustering techniques with UAV mobility to refine routing strategies in WSNs.The proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads(CHs).This system is primarily aimed at reducing energy consumption through meticulously planned routing and path determination.Employing a greedy algorithm for inter-cluster dialogue,our framework orchestrates CHs into an efficient communication chain.Through comparative analysis,the proposed model demonstrates a marked improvement over traditional methods such as the cluster chain mobile agent routing(CCMAR)and the energy-efficient cluster-based dynamic algorithms(ECCRA).Specifically,it showcases an impressive 15%increase in energy conservation and a 20%reduction in data transmission time,highlighting its advanced performance.Furthermore,this paper investigates the impact of various network parameters on the efficiency and robustness of the WSN,emphasizing the vital role of sophisticated computational strategies in optimizing network operations.

Elevating Image Steganography:A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential priority.To overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure communications.Most of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB substitution.In this work,we have an approach that utilizes a combinationofMost SignificantBit(MSB)matching andLeast Significant Bit(LSB)substitution.The proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three bits.The proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio(PSNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment capacity.The achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak Signal-to-Noise Ratio(PSNR)of 37 dB.These findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

M_(4)X_(3) MXenes:Application in Energy Storage Devices

MXene has garnered widespread recognition in the scientific com-munity due to its remarkable properties,including excellent thermal stability,high conductivity,good hydrophilicity and dispersibility,easy processability,tunable surface properties,and admirable flexibility.MXenes have been categorized into different families based on the number of M and X layers in M_(n+1)X_(n),such as M_(2)X,M_(3)X_(2),M_(4)X_(3),and,recently,M_(5)X_(4).Among these families,M_(2)X and M_(3)X_(2),par-ticularly Ti_(3)C_(2),have been greatly explored while limited studies have been given to M_(5)X_(4)MXene synthesis.Meanwhile,studies on the M_(4)X_(3)MXene family have developed recently,hence,demanding a compilation of evaluated studies.Herein,this review provides a systematic overview of the latest advancements in M_(4)X_(3)MXenes,focusing on their properties and applications in energy storage devices.The objective of this review is to provide guidance to researchers on fostering M_(4)X_(3)MXene-based nanomaterials,not only for energy storage devices but also for broader applications.

Protocol for lower back pain management: Insights from the French healthcare system

In this editorial we comment on the article published in a recent issue of the World Journal of Clinical Cases.This article described a novel ultrasound-guided lateral recess block approach in treating a patient with lateral recess stenosis.The impact of spinal pain-related disability extends significantly,causing substantial human suffering and medical costs.Each county has its preferred treatment strategies for spinal pain.Here,we explore the lower back pain(LBP)treatment algorithm recommended in France.The treatment algorithm for LBP recommended by the French National Authority for Health emphasizes early patient activity and minimal medication use.It encourages the continuation of daily activities,limits excessive medication and spinal injections,and incorporates psychological assessments and non-pharmacological therapies for chronic cases.However,the algorithm may not aggressively address acute pain in the early stages,potentially delaying relief and increasing the risk of chronicity.Additionally,the recommended infiltrations primarily involve caudal epidural steroid injections,with limited consideration for other injection procedures,such as transforaminal or interlaminar epidural steroid injections.The fixed follow-up timeline may not accommodate patients who do not respond to initial treatment or experience intense pain,potentially delaying the exploration of alternative therapies.Despite these limitations,understanding the strengths and weaknesses of the French approach could inform adaptations in LBP treatment strategies globally,potentially enhancing patient outcomes and satisfaction across diverse healthcare systems.

Differences between the healthcare systems of Quebec and France for the treatment of pain due to spinal disorders

In Quebec,Canada,the public healthcare system offers free medical services.However,patients with spinal pain often encounter long waiting times for specialist appointments and limited physiotherapy coverage.In contrast,private clinics provide expedited care but are relatively scarce and entail out-of-pocket expenses.Once a patient with pain caused by a spinal disorder meets a pain medicine specialist,spinal intervention is quickly performed when indicated,and patients are provided lifestyle advice.Transforaminal epidural steroid injections are frequently administered to patients with radicular pain,and steroid injections are administered on a facet joint to control low back or neck pain.Additionally,medial branch blocks are performed prior to thermocoagulation.France’s universal healthcare system ensures accessibility at controlled costs.It emphasizes physical activity and provides free physical therapy services.However,certain interventions,such as transforaminal and interlaminar epidural injections,are not routinely used in France owing to limited therapeutic efficacy and safety concerns.This underutilization may be a potential cause of chronic pain for many patients.By examining the differences,strengths,and weaknesses of these two systems,valuable insights can be gained for the enhancement of global spinal pain management strategies,ultimately leading to improved patient outcomes and satisfaction.

An Enhanced Integrated Method for Healthcare Data Classification with Incompleteness

In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks.Traditional approaches often rely on statistical methods for imputation,which may yield suboptimal results and be computationally intensive.This paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved accuracy.Conventional classification methods are ill-suited for incomplete medical data.To enhance efficiency without compromising accuracy,this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete data.Initially,the linear interpolation imputation method alongside an iterative Fuzzy c-means clustering method is applied and followed by a classification algorithm.The effectiveness of the proposed approach is evaluated using multiple performance metrics,including accuracy,precision,specificity,and sensitivity.The encouraging results demonstrate that our proposed method surpasses classical approaches across various performance criteria.