High Detection Rate Research Articles

Design and performance analysis of integrated sensing and communication scheme based on LoRa signals

LoRa (Long Range) has garnered widespread adoption in Internet of Things (IoT) communications due to its extensive transmission range and robust resistance to interference. Furthermore, its capability to linearly discern deviations across both frequency and time domains renders it an ideal signal for sensing applications. Consequently, this article proposes an Integrated Sensing and Communication (ISAC) scheme based on the LoRa signal. On the communication side, while the modulation and demodulation processes of the LoRa signal are currently kept confidential, this article has theoretically derived its principles and further implemented the communication functionality of LoRa through experimental simulations. On the sensing side, through theoretical derivation and experimental simulation, the influence of different modulation information on the peak amplitude and position of pulse compression was analyzed. Two signal processing schemes are proposed to overcome the impact of modulation information, thereby enabling the sensing function. The communication and sensing performance of the proposed ISAC scheme was evaluated. Experimental results demonstrated that, even in low signal-to-noise ratio (SNR) environments, the communication function maintained a low bit error rate (BER), while the sensing function achieved a high target detection rate, both of which exhibited excellent performance.

Evaluation of testing face-mask filter samples with LAMP shows high rates of detection in pulmonary TB.

<sec><title>BACKGROUND</title>Detection of Mycobacterium tuberculosis (MTB) in bioaerosols derived from patients with active pulmonary TB is a potential alternative diagnostic method for patients with presumed TB who cannot expectorate sputum.</sec><sec><title>OBJECTIVE</title>To assess the efficacy of a bioaerosol particle collection method to capture MTB and diagnose TB.</sec><sec><title>METHODS</title>A mask-like filter holder (3D mask) with a water-soluble gelatine filter (GF) and one containing a water-insoluble polypropylene filter (PPF) were prepared. Eligible patients wore the 3D mask with GF or PPF within 3 days of starting anti-TB drugs. The GF and PPF filters were collected after 2 and 8 h. DNA was extracted from the filter samples and tested using loop-mediated isothermal amplification (LAMP).</sec><sec><title>RESULTS</title>Filter samples were collected from 57 and 20 patients with and without active pulmonary TB, respectively. The GF and PPF sensitivity was 76.2% and 83.3%, respectively. The specificity of both methods was 100%. Of the 57 patients diagnosed with non-expectorated sputum samples, including suction phlegm, gastric lavage, and bronchial lavage fluid, 55.6% and 50.0% were positive by GF and PPF, respectively.</sec><sec><title>CONCLUSION</title>We present a 3D mask filter sampling method for exhaled bioaerosol particles that can be used in clinical practice to diagnose patients with presumed TB.</sec>.

MA02.04 High Detection Rate of Blood MicroRNA Test in Lung Cancer Screening Eligible Individuals.

MA02.04 High Detection Rate of Blood MicroRNA Test in Lung Cancer Screening Eligible Individuals.

Indocyanine green and methylene blue dye guided sentinel lymph node biopsy in patients with penile cancer (PeCa): results of 50 inguinal basins assessed at a single institution in India.

The primary aim of this study was to validate the reliability, sensitivity and safety profile of novel combination of ICG- methylene blue dye as an SN tracer for PeCa. This is a validation and non-randomised prospective observational study involving 25 patients (50 inguinal basins) who underwent SLNB where in ICG and methylene blue were used for localisation. The patients with clinically node negative groins were recruited in the study. SNs were identified intraoperatively using near infrared fluorescence imaging (NIRF Imaging system, SPY-PHI, Stryker, Sweden) and blue dye. The numbers of SNs identified by each tracer and the rates of complications and nodal recurrence during the followup. Overall 137 SNs were identified intraoperatively. Among the 137 SNs excised fluorescence, blue dye and Combined (blue + green) identified 57(41.6%), 27 (19.7%), and 51 (37.2%), respectively. The average number of SLNs removed per patient was 5 (range, 1-11) with sentinel lymph nodes detection rate at 94% (47/50). Seven patients had malignancy on SLNB and underwent ipsilateral radical inguinal lymphadenectomy. One patient had false negative SN and positive node in modified inguinal lymphadenectomy specimen. No adverse events were observed in all cases. The Novel combination of ICG fluorescence-Methylene blue dye technique is simple, reliable and safe. Moreover, it demonstrates a high SLN detection rate with a low false-negative rate, and it avoids radiation exposure.

Real or virtual: a video conferencing background manipulation-detection system

AbstractIn the past few years, the popularity and wide use of video conferencing software enjoyed exponential growth in market size. This technology enables participants in different geographic regions to have a virtual face-to-face meeting. Additionally, it allows participants to utilize virtual backgrounds to hide their real environment with privacy concerns or to reduce distractions, particularly in professional settings. In scenarios where the users should not hide their actual locations, they may mislead other participants into assuming that the displayed virtual backgrounds are real. In this paper, we propose a new publicly-available dataset of virtual and real backgrounds in video conferencing software (e.g., Zoom, Google Meet, Microsoft Teams). The presented archive was evaluated by an exhaustive series of tests and scenarios using two well-known features extraction methods: CRSPAM1372 and six co-mat. The first verification scenario considers the case where the detector is unaware of manipulated frames (i.e., the forensically-edited frames are not part of the training set). A model trained on zoom frames that were tested with Google Meet frames can detect real background images from virtual ones in video conferencing software with 99.80% detection accuracy. Furthermore, it is possible to distinguish virtual from real backgrounds in videos created for videoconferencing software at a high detection rate of approximately 99.80%. According to our conclusions, the proposed method greatly enhanced the detection accuracy and resistance against diverse adversarial conditions, making it a reliable technique for classifying actual as opposed to virtual backgrounds in video communications. Given the described dataset provided and some preliminary experiments that we performed, we expect that it will lead to more future research in this domain.

Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study.

Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse drug event (ADE) signals. As different aspects of a patient's status are stored in different types of documents, we propose an NLP system capable of processing 6 types of documents: physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. This study aimed to investigate the system's performance in detecting ADEs by evaluating the results from multitype texts. The main objective is to detect adverse events accurately using an NLP system. We used data written in Japanese from 2289 patients with breast cancer, including medication data, physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. Our system performs 3 processes: named entity recognition, normalization of symptoms, and aggregation of multiple types of documents from multiple patients. Among all patients with breast cancer, 103 and 112 with peripheral neuropathy (PN) received paclitaxel or docetaxel, respectively. We evaluate the utility of using multiple types of documents by correlation coefficient and regression analysis to compare their performance with each single type of document. All evaluations of detection rates with our system are performed 30 days after drug administration. Our system underestimates by 13.3 percentage points (74.0%-60.7%), as the incidence of paclitaxel-induced PN was 60.7%, compared with 74.0% in the previous research based on manual extraction. The Pearson correlation coefficient between the manual extraction and system results was 0.87 Although the pharmacist progress notes had the highest detection rate among each type of document, the rate did not match the performance using all documents. The estimated median duration of PN with paclitaxel was 92 days, whereas the previously reported median duration of PN with paclitaxel was 727 days. The number of events detected in each document was highest in the physician's progress notes, followed by the pharmacist's and nursing records. Considering the inherent cost that requires constant monitoring of the patient's condition, such as the treatment of PN, our system has a significant advantage in that it can immediately estimate the treatment duration without fine-tuning a new NLP model. Leveraging multitype documents is better than using single-type documents to improve detection performance. Although the onset time estimation was relatively accurate, the duration might have been influenced by the length of the data follow-up period. The results suggest that our method using various types of data can detect more ADEs from clinical documents.

Safety of Intraoperative Cell Salvage in Two-Stage Revision of Septic Hip Arthroplasties.

(1) Background: The aim of this study was to evaluate the safety of intraoperative cell salvage (ICS) during reimplantation in the two-stage revision of septic hip arthroplasties. (2) Methods: As part of an internal quality control study, blood cultures were taken from the processed ICS blood during reimplantation and examined for possible bacterial load (study group). Due to a high rate of bacterial detection with uncertain clinical significance, consecutive ICS samples were also examined from patients undergoing aseptic revision hip arthroplasty (control group). Microbiological samples, patient and surgical characteristics and the follow-up data were analyzed retrospectively. (3) Results: 9 out of 12 (75%) patients in the study group and 5 out of 8 (63%) patients in the control group had positive ICS blood cultures. There was no significant difference between the groups (p = 0.642). The initial pathogens causing the periprosthetic joint infection (PJI) were not detected, but the bacterial spectrum resembled skin flora, with a high proportion of coagulase-negative staphylococci. No complications due to possible bloodstream-associated infections were observed. In summary, the detected pathogens were interpreted as contamination without clinical significance. (4) Conclusions: ICS in the context of reimplantation was considered a safe and recommendable procedure to optimize patient blood management.

Multi-marker analysis of circulating tumor cells in localized intermediate/high-risk and metastatic prostate cancer

AbstractCirculating tumor cells (CTCs) are an established prognostic marker in metastatic prostate cancer (PrC) but have received little attention in localized high-risk disease. Peripheral blood was obtained from patients with early intermediate and high-risk PrC (n = 15) at baseline, after radiotherapy, and during follow-up, as well as from metastatic PrC patients (n = 23). CTCs were enriched using the microfluidic Parsortix® technology. CTC-related marker were quantified with qPCR and RNA in-situ hybridization (ISH). Positivity and associations to clinical parameters were assessed using McNemar test, Fisher Exact test or log-rank test. The overall positivity was high in both cohorts (87.0% metastatic vs. 66.7% early at baseline). A high concordance of qPCR and RNA ISH was achieved. In metastatic PrC, PSA and PSMA were prognostic for shorter overall survival. In early PrC patients, an increase of positive transcripts per blood sample was observed from before to after radiation therapy, while a decrease of positive markers was observed during follow-up. CTC analysis using the investigated qPCR marker panel serves as tool for achieving high detection rates of PrC patient samples even in localized disease. RNA ISH offers the advantage of confirming these markers at the single cell level. Employing the clinically relevant marker PSMA, our CTC approach can be used for diagnostic purposes to screen patients profiting from PSMA-directed PET-CT or PSMA-targeted therapy.

Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study

BackgroundTo evaluate the stand-alone efficacy and improvements in diagnostic accuracy of early-career physicians of the artificial intelligence (AI) software to detect large vessel occlusion (LVO) in CT angiography (CTA).MethodsThis multicenter...

Enhancing fault detection in multivariate industrial processes: Kolmogorov–Smirnov non-parametric statistical approach

The accurate detection of abnormal events in modern process plants is extremely important. The detection of faults of small magnitude and in a noisy process environment is still a challenge that many industries face. In this paper, a Kolmogorov–Smirnov (KS) based non-parametric statistical fault indicator is proposed to identify a variety of sensor faults in process plants. The data collected from most modern process plants are randomly varying and non-Gaussian, due to which the multivariate scheme based on Independent Component Analysis (ICA) is considered. The KS-based indicator is amalgamated with the ICA multivariate model, which yields a novel ICA-KS-based fault detection (FD) scheme. The KS statistical indicator compares any two distributions and checks if they are similar or dissimilar. The potential of the KS indicator is extended in the FD domain, where the residuals of training and testing data are compared in a sliding window. The ability of the proposed ICA-KS-based FD strategy is validated on a simulated Distillation column (DC) process and the benchmark Tennessee Eastman (TE) process to identify a variety of sensor faults. The simulation results demonstrate the effectiveness of the detection performance of the ICA-KS scheme, which outperforms conventional FD-based methods with a high detection rate.

Pesticide residues and associated health effects in marketed fruits in Saudi Arabia

AimThis study evaluated the pesticide residues in some fruits collected from different markets in Saudi Arabia (SA) and determined potential health risks associated with them. MethodsConcentrations of pesticide residues in 12 types of fruits from local markets in SA from 2020 to 2022 were collected and evaluated. Multiple residue extraction method QuEChERS followed by LC-MS/MS and GC–MS/MS, were used to analyze 161 samples. ResultsOnly 10 out of 161 samples (6.2 %) were free of pesticides. A total of 132 (87.4 %) pesticide residues were below MRLs, with 19 (12 %) of samples exceeding MRLs. Detected pesticide residues belonged to different chemical classes of pesticides including organophosphates, pyrethroids, organochlorines, neonicotinoids and fungicides. Risk assessment of human exposure to pesticides via the intake of the fruit types was performed. Hazard index (HI) for most fruit types were found to be less than 1. Oranges, grapes and pomegranates were the most consumed fruit types (31.6 g/day,15.8 g/day,10.8 g/day) and were contaminated with pesticide residues. Fluopyram, imazalil, chlorpyrifos, finamiphos and indoxacarb had HIs (1.32, 2.76,3.6,3.6,1.5) showed high risk index suggesting risk for systemic toxicity in consumers dependent on the amount of consumption. ConclusionIn summary, high detection rate of pesticide residues was found in different fruits sold in local markets in SA. Regular biomonitoring programs for food crops in SA markets should be enforced, particularly in identified crops with His >1 to increase food safety within the SA community.

Tracking Whale Calls in the Lower St. Lawrence Seaway at Land Seismometers

The Lower St. Lawrence Seaway (LSLS) is critical to Canada’s economy both as part of a major marine shipping corridor and a site of intensive fishing. Every year, fin whales and blue whales frequent the LSLS feeding ground. Understanding the mechanisms driving whale habitat usage is key for making informed decisions on shipping and fishing, reducing whale collision risks and mitigating noise pollution. We detect whales in the LSLS with land seismometers by using a method that relies on the intervals of the regularly repeating low frequency calls. The resulting catalogue contains 14,076 fin whale detections and 3,739 blue whale detections between February 2020 and January 2022. These detections follow the overall pattern of hydrophones, with most detections from fall to early winter in the Estuary and until mid-winter/spring in the Gulf. High detection rates in the Northwest Gulf throughout the winter months demonstrate that this region is potentially utilized year-round. This labelled catalogue may be suitable for developing a deep learning-based whale call detection algorithm. Making use of seismometers and deep learning can increase whale monitoring coverage within the LSLS and elsewhere.

Optimization of iron flocculation for enrichment of CyHV-2 in aquaculture water

Cyprinid herpesvirus 2 (CyHV-2) is an important infectious virus endangering the farmed Carassius species industry. The enrichment and identification of CyHV-2 in the water is a vital means of early warning diagnostics, which is helpful to aquatic diseases prevention and control. In this study, we employed and optimized iron flocculation to enrich the concentrations of CyHV-2 in aquaculture water. Different Fe3+ concentrations (0.5, 1.0, and 10.0 mg/L), various membrane filters (mixed cellulose ester, glass fiber, nylon microporous filter membrane), different elution buffers containing reductants (ascorbate, citrate, DL-malate, and their combinations with EDTA or TE buffer) were compared to check the recovery yield of CyHV-2. Viral genome quantitation was determined using quantitative real-time PCR. The results showed that Fe3+ concentration of 1.0 mg/L, the glass fiber and citrate-TE were determined to have high efficiency and stable recovery yield. To evaluate infectious CyHV-2 viral titres, crucian carps (Carassius auratus) were intraperitoneally injected with CyHV-2. The mortality rate was 100 % at 9 days postinoculation (dpi) with the 96.7 % detection of CyHV-2 in the pooled tissues. The histopathological phenotype showed necrotic cell death in the liver, spleen and kidney. The CyHV-2 genome was ranging from 101.1 to 107.5 copies/μl in the deceased fish, and 101.4 to 103.0 copies/μl in the feeding water at various stages from latent infection to onset of disease. The field samples from Huzhou, Zhejiang Province on June 4th and 7th had higher detection rates, 87.5 % and 100 % respectively, corresponding to higher CyHV-2 detected in the aquaculture water. CyHV-2 viral load in cultured waters tends to increase prior to fish death, which provides a new indicator for the prediction of fish diseases. In summary, we have established a unified operational standard for enrichment of CyHV-2 in the aqueous environment by iron flocculation.

Achieving sub-millisievert CT colonography for accurate colorectal tumor detection using smart examination protocols: a prospective self-controlled study.

To assess the feasibility of combining Auto-kVp selection technique, higher preset ASIR-V and noise index (NI) to realize individualized sub-mSv CT colonography (CTC) for accurate colorectal tumor detection and localization. Ninety patients with suspected colorectal cancer (CRC) were prospectively enrolled to undergo standard dose CTC (SDCTC) in the prone and ultra-low dose CTC (ULDCTC) in the supine position. SDCTC used 120 kVp, preset ASIR-V of 30%, SmartmA for a NI of 13; ULDCTC used Auto-kVp selection technique with 80 or 100 kVp, preset ASIR-V of 60%, SmartmA for a NI of 13 for 80 kVp, and NI of 15 for 100 kVp. The effective dose (ED), image quality [signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of colorectal neoplasms] between the two protocols were compared and the accuracies of tumor locations were evaluated for CTC in comparison with the surgery results. The mean ED of the ULDCTC-80 kVp subgroup was 0.70 mSv, 71.43% lower than the 2.45mSv for the 120 kVp group, while that of the ULDCTC-100 kVp subgroup was 0.98mSv, 73.00% lower than the 3.63mSv for the 120 kVp group (P < 0.001). The tumor SNR and CNR of the ULDCTC were higher than those of SDCTC (P < 0.05), while there was no difference in the subjective image quality between them with good inter-observer agreement (Kappa: 0.805-0.923). Both SDCTC and ULDCTC groups had high detection rate of colorectal tumors, along with good consistency in determining tumor location compared with surgery reports (Kappa: 0.718-0.989). The combination of Auto-kVp selection, higher preset ASIR-V and NI achieves individualized sub-mSv CTC with good performance in detecting and locating CRC with surgery and consistent results between SDCTC and ULDCTC.

A lightweight intrusion detection algorithm for IoT based on data purification and a separable convolution improved CNN

With the rapid development of the IoT (Internet of Things), the network data present the characteristics of large volume and high dimension. Convolutional neural networks (CNNs) have become one of the most important intrusion detection methods due to their advantages in processing high-dimensional data. The conventional intrusion detection model based on CNN lacks an effective data purification means in the process of converting unstructured data into image data, and too many parameters are generated due to the complex structure of the model in the training process, leading to the problems of high time complexity and low detection rate of the model, which limits the application of the CNN in intrusion detection of the IoT. First, based on the principle of liquid molecular distillation, a data purification algorithm (DPA) for unstructured data is proposed in this paper, which reduces the "redundant" data generated in the process of converting unstructured data to image data. Second, based on the rigid-motion convolution principle of a separable wavelet, separable convolution is used to improve the CNN structure, and then a lightweight detection algorithm LSCNN (lightweight CNN based on separable convolution) is developed to reduce the number of parameters in the network structure and improve the time efficiency and accuracy of the algorithm. The experimental results on real intrusion detection datasets show that the LSCNN trained on DPA purified data has higher time efficiency and detection accuracy than the conventional CNN, and compared with the conventional machine learning algorithm, it has higher accuracy.

Results of a Prospective Randomized Multicenter Study Comparing Indocyanine Green (ICG) Fluorescence Combined with a Standard Tracer Versus ICG Alone for Sentinel Lymph Node Biopsy in Early Breast Cancer: The INFLUENCE Trial.

For clinically node-negative early breast cancer patients, sentinel lymph node biopsy (SLNB) using dual localization with blue dye and radioisotope (RI) is currently standard of care. Documented disadvantages with these tracers have prompted exploration of alternative agents such as fluorescent indocyanine green (ICG), which demonstrates high detection rates combined with other tracers. Results of a randomized study evaluating ICG as a single tracer for SLN identification are presented. Overall, 100 patients with unilateral, clinically node-negative, biopsy-proven invasive breast cancer (≤5cm) scheduled for SLNB were recruited in two separate randomized cohorts, with 50 patients receiving ICG alone. Cohort 1 received ICG alone (n=25) or combined with RI [Technetium99] (n=25), while Cohort 2 received ICG alone (n=25) or combined with blue dye (n=25). The primary outcome was sensitivity for SLN identification. Among evaluable patients (n=97), the overall SLN identification rate was 96.9% (ICG alone = 97.9%; ICG + RI = 100%; ICG + blue dye = 92%). Node positivity rates were 14.9% for ICG alone, 16% for ICG combined with RI, and 20% for ICG combined with blue dye. There were no significant differences (p<0.05) in performance parameters, with ICG alone being non-inferior to tracer combinations for procedural node positivity rates when adjusted for specific factors. These results support potential use of ICG as a sole tracer agent for routine SLNB, thereby avoiding disadvantages of RI and/or blue dye. The latter can be safely withheld as a co-tracer without compromising detection of positive nodes in primary surgical patients.

Monitoring of ketamine-based emerging contaminants in wastewater: a direct-injection method and fragmentation pathway study

The ketamine (KET) and its analogs consumed by humans are becoming emerging contaminants (ECs), as they at present in surface waters after being carried through wastewater systems. Drugs in wastewater can be analyzed using the direct-injection method, a simple wastewater analysis (WWA) method that can provide objective, continuous and nearly to real-time findings. This article describes an ultra-high-pressure liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method for the simultaneous quantification and confirmation of seven KET-based ECs in wastewater by direct injection. After optimization of the UPLC–MS/MS and sample pretreatment conditions, the method was validated and applied to samples (n = 157) collected from several wastewater treatment plants (WWTPs) in southern China in which KET had the highest detection rate. The established direct-injection method was not only simple to perform but also had better sensitivity, shorter detection times, and analyzed more KET-based ECs than currently published methods, meeting the requirements for the monitoring and high-throughput analysis of common KET-based ECs. We also analyzed the fragmentation pathway of KET-based ECs to obtain product ion information on other unknown substances. Additional studies are needed to establish a comprehensive direct-injection screening method of ECs in wastewater on model-based assessment.

AMAR-seq: Automated Multimodal Sequencing of DNA Methylation, Chromatin Accessibility, and RNA Expression with Single-Cell Resolution.

Parallel single-cell multimodal sequencing is the most intuitive and precise tool for cellular status research. In this study, we propose AMAR-seq to automate methylation, chromatin accessibility, and RNA expression coanalysis with single-cell precision. We validated the accuracy and robustness of AMAR-seq in comparison with standard single-omics methods. The high gene detection rate and genome coverage of AMAR-seq enabled us to establish a genome-wide gene expression regulatory atlas and triple-omics landscape with single base resolution and implement single-cell copy number variation analysis. Applying AMAR-seq to investigate the process of mouse embryonic stem cell differentiation, we revealed the dynamic coupling of the epigenome and transcriptome, which may contribute to unraveling the molecular mechanisms of early embryonic development. Collectively, we propose AMAR-seq for the in-depth and accurate establishment of single-cell multiomics regulatory patterns in a cost-effective, efficient, and automated manner, paving the way for insightful dissection of complex life processes.

Impact of Indocyanine Green Dose on Sentinel Lymph Node Mapping in Cervical Cancer: A Systematic Review.

Over the past decade, SLN mapping has become increasingly important in cervical cancer surgery. ICG is the most commonly used tracer due to its high bilateral detection rates, ease of use, and safety. However, there is no consensus on the optimal ICG dose, leading to variability in outcomes. This systematic review aims to evaluate the impact of different ICG doses on SLN detection in early-stage cervical cancer, identifying the most effective and safe dose for clinical practice. A comprehensive search was conducted in MEDLINE/PubMed up to May 2024. Studies included assessed SLN mapping using ICG in stage IA2-IIA/IIB cervical cancer. Exclusions were applied to studies not reporting ICG dose or using multiple tracers without dose-specific results. Twelve studies were included, with ICG concentrations ranging from 0.25 mg/mL to 25 mg/mL and injection volumes from 1 to 10 mL. Overall SLN detection rates ranged from 88% to 100%, while bilateral detection rates varied between 74.1% and 98.5%. The most consistent results were obtained with an ICG concentration of 1.25 mg/mL and a 4 mL injection volume. In conclusion, an ICG concentration of 1.25 mg/mL with a 4 mL injection volume is recommended for effective SLN mapping in cervical cancer, achieving high detection rates with minimal variability. Standardizing this dose in clinical practice is suggested to improve reproducibility and outcomes.

Enhanced Pharmacy Service Delivery Through a Pharmacy Information System at a Medical Center: A Case Study.

A pharmacy information system (PIS) is a crucial tool for preventing errors and enhancing patient safety. This study aims to assess the influence of a PIS on workflow and medication errors (MEs) within the pharmacy department of a medical city in Saudi Arabia. The analysis encompasses an evaluation of the current workflow within pharmacy modules (in-patient, out-patient, and clinical pharmacy modules) and an exploration of associated challenges and inefficiencies. The study employed both qualitative and quantitative methodologies, incorporating structured interview techniques and the review of system records, such as logs, incident reports, and ME databases. Respondents recognized the benefits of the PIS, including the management of high-quality real-time data (26%), reduction of MEs (25%), acceleration of healthcare practices (23%), and absence of space-time constraints (14%). The study highlighted the role of PIS in addressing medication stock control and shortage issues, thereby improving overall medication availability. Furthermore, PIS significantly enhanced safety (93.3%), efficiency (80%), reliability, accuracy, ease of use (56.7%, 56.7%), and cost-effectiveness (53.7%). Following the implementation of the PIS, there was an increase in ME reporting, indicating improved error detection and management. The research revealed an increase in ME reporting rates in hospitals after PIS installation, attributed to improved medication management processes resulting in higher detection rates. As healthcare facilities increasingly embrace electronic medical records, the understanding of patient care quality will be significantly impacted. Consequently, further research is warranted to explore the role of PIS in reporting, detecting, analyzing, and mitigating MEs, as well as their influence on the work environment to promote a secure and efficient patient journey.