Diagnostic Algorithm Research Articles

Optimized data driven fault detection and diagnosis in chemical processes

Fault detection and diagnosis (FDD) is crucial for ensuring process safety and product quality in the chemical industry. Despite the large amounts of process data recorded and stored in chemical plants, most of them are not well-labeled, and their conditions are not adequately specified. In this study, an optimized data-driven FDD model was developed for a chemical process based on automatic clustering algorithms. Due to data preprocessing importance, feature selection was performed by a non-dominated sorting genetic algorithm (NSGAII) based on k-means clustering. The optimal subset of features is selected by comparing clustering results for each subset. The performance of the proposed feature selection method was compared with the Fisher discriminant ratio (FDR), and XGBoost methods. The t-distributed stochastic neighbor embedding (t-SNE), Isomap, and KPCA dimension reduction methods were also employed for feature extraction. Finally, automatic clustering was performed based on metaheuristic algorithms for fault detection and diagnosis. Results were compared with non-automatic clustering methods. The performance of the proposed method was evaluated by examining the Tennessee Eastman and four water tank processes as case studies. The results showed that the proposed method is reliable and capable of online and offline chemical process fault detection and diagnosis. As a result, the findings of this study can be used to stabilize the operation of chemical processes.

Complications following surgical treatment of ankle fractures in the elderly: can they be avoided?

Background Following surgical treatment of ankle fractures, geriatric patients face high complication rates (CR) in literature. Commonly used diagnostic and treatment algorithms fail to consider requirements of ageing patients which increases the risk of postoperative complications. Objective Present study critically evaluated surgical management of ankle fractures in patients over 65 years old, with focus on identifying modifiable risk factors and effective comorbidity management strategies. Methods We conducted a retrospective single-center study on patients who underwent surgical treatment of an ankle fracture. Based on their age, participants were divided into non-geriatric patients (NGP<65y) and geriatric patients (GP≥65y). We analyzed overall CR and number of minor and major complications in relation to timing of surgery, biological sex, injury pattern, osteosynthesis, pre-existing medical conditions, and postoperative care. Results 402 patients were included. GP encountered significantly higher overall (p<0.001), minor (p<0.001) and major (p=0.003) complications. They presented more complex, displaced and open fractures. Predominant factor contributing to higher CR in NGP and markedly in GP was concomitant diseases, presenting a strong OR of 19,290 (p<0.001) and 17,022 (p<0.001). Delaying surgery and managing comorbidities preoperatively had a favorable impact. Conclusion We revealed a high significant correlation between pre-existing medical conditions and postoperative results. To ascertain viability of delayed surgery in facilitating additional diagnostics and treatment of comorbidities, further comparative trials with a larger cohort are imperative.

Emergencies in infectious diseases

This article aims to provide an overview of common and high-impact medical emergencies that require prompt and effective infectious diseases management. In the described clinical scenarios of malaria, sepsis, necrotizing fasciitis, and meningitis the authors have emphasized the crucial importance of rapid and accurate diagnosis, as well as appropriate treatment from the perspective of infectious diseases. All of these emergencies demand ahigh degree of clinical suspicion for accurate diagnosis. Some of them also necessitate the involvement of other medical disciplines, such as neurology in the case of meningitis or surgery for necrotizing fasciitis. Additionally, implementing the right empiric antibiotic regimen or, in the case of malaria, antiparasitic treatment is crucial for improving patient outcomes. As patients with these diagnoses may present at any outpatient department, and efficient and quick management is essential, adeep understanding of diagnostic algorithms and potential pitfalls is of the utmost importance.

From standard therapies to monoclonal antibodies and immune checkpoint inhibitors - an update for reconstructive surgeons on common oncological cases.

Malignancies represent a persisting worldwide health burden. Tumor treatment is commonly based on surgical and/or non-surgical therapies. In the recent decade, novel non-surgical treatment strategies involving monoclonal antibodies (mAB) and immune checkpoint inhibitors (ICI) have been successfully incorporated into standard treatment algorithms. Such emerging therapy concepts have demonstrated improved complete remission rates and prolonged progression-free survival compared to conventional chemotherapies. However, the in-toto surgical tumor resection followed by reconstructive surgery oftentimes remains the only curative therapy. Breast cancer (BC), skin cancer (SC), head and neck cancer (HNC), and sarcoma amongst other cancer entities commonly require reconstructive surgery to restore form, aesthetics, and functionality. Understanding the basic principles, strengths, and limitations of mAB and ICI as (neo-) adjuvant therapies and treatment alternatives for resectable or unresectable tumors is paramount for optimized surgical therapy planning. Yet, there is a scarcity of studies that condense the current body of literature on mAB and ICI for BC, SC, HNC, and sarcoma. This knowledge gap may result in suboptimal treatment planning, ultimately impairing patient outcomes. Herein, we aim to summarize the current translational endeavors focusing on mAB and ICI. This line of research may serve as an evidence-based fundament to guide targeted therapy and optimize interdisciplinary anti-cancer strategies.

A practical ligament-based diagnostic system for cure of pelvic symptoms and prolapse.

The Integral Theory Paradigm (ITP) has a 25-year track record of successfully treating bladder/bowel/pain symptoms caused by laxity in specific ligaments, even when the prolapse is minimal. The ITP-based treatment involves ligament support and can be nonsurgical or daycare surgical. An accurate diagnostic protocol is required. The Integral Theory Diagnostic system is performed in an outpatient setting. It a step-by-step "how to" resource for clinicians who wish to learn a practical anatomical diagnostic method which can quickly and accurately identify a ligament cause for bladder/bowel/pain symptoms, and therefore, potentially cure them. The structured ITP diagnosis flow chart uses symptoms to diagnose anatomical defects. It comprises 4 related steps. The ITP is holistic, and bladder, bowel, pain symptoms co-occur. The first step, therefore, is to establish all possible symptoms for transfer to the Diagnostic Algorithm which is the second step. Because patients complain of one main symptom, other symptoms must be located by direct questioning, using the Diagnostic Algorithm as an aide memoire, or a questionnaire to locate bladder, bowel, pain symptoms. Second step: symptoms are placed into 3 anatomical zones: anterior zone, pubourethral ligament (PUL) [stress urinary incontinence (SUI)]; middle zone, cardinal ligament (CL) (transverse defect cystocele); posterior zone, uterosacral ligament (USL) (uterine prolapse and enterocele). The third step is a vaginal examination to confirm the ligament damage (prolapses) in the three zones predicted by the algorithm. The fourth step is "simulated operations" (mechanical support of specific ligaments per vaginam) to validate the particular ligament indicated by the diagnostic algorithm, is indeed causing that symptom. For SUI, a hemostat test at midurethra supports PUL vaginally to stop urine loss on coughing; the lower blade of a bivalve speculum gently inserted into the vagina can relieve urge and pain.

Chronic pelvic pain of "unknown origin" in the female.

The remit of this review is confined to the experimental scientific works and surgeries based on the Integral Theory Paradigm (ITP). Chronic pelvic pain (CPP) is a major societal problem which is said to occur in up to 20% of women. The pathogenesis of CPP of "unknown origin" is said to be unknown and CPP is said to be incurable. According to the ITP, however, CPP is said to be mainly caused by the inability of loose or weak uterosacral ligaments (USLs) to mechanically support visceral nerve plexuses (VPs), T11-L2 and S2-4. These fire off de novo impulses, interpreted by the cortex as pain coming from the end organs. CPP, when it occurs simultaneously in multiple pelvic sites, is associated with uterine/apical prolapse (often minimal) and bladder symptoms such as overactive bladder (OAB), nocturia, retention. This combination of symptoms was described in 1993 as the "posterior fornix syndrome" (PFS). As such, CPP when associated with the PFS, is potentially curable by surgical repair of USLs. However, patients with CPP generally complain only of one symptom, CPP. This is known as the "Pescatori iceberg" effect. Other PFS symptoms are "under the surface" and must be sought out by direct questioning. The diagnostic algorithm is helpful in locating other associated symptoms. Definitive diagnosis of CPP, caused by USL laxity, is immediate alleviation of pain by mechanical support of USLs by using the speculum test or by tampons in the posterior fornix. Treatment of CPP can be non-surgical, by strengthening USLs by squatting exercises, supporting USLs mechanically with tampons or USL surgery. Coexisting bladder symptoms are (variously) improved or cured. URL for CPP https://www.pelviperineology.org/volume/36/issue/3.

Pediatric Ischemic Stroke: Clinical and Paraclinical Manifestations—Algorithms for Diagnosis and Treatment

Childhood stroke can lead to lifelong disability. Developing algorithms for timely recognition of clinical and paraclinical signs is crucial to ensure prompt stroke diagnosis and minimize decision-making time. This study aimed to characterize clinical and paraclinical symptoms of childhood and neonatal stroke as relevant diagnostic criteria encountered in clinical practice, in order to develop algorithms for prompt stroke diagnosis. The analysis included data from 402 pediatric case histories from 2010 to 2016 and 108 prospective stroke cases from 2017 to 2020. Stroke cases were predominantly diagnosed in newborns, with 362 (71%, 95% CI 68.99–73.01) cases occurring within the first 28 days of birth, and 148 (29%, 95% CI 26.99–31.01) cases occurring after 28 days. The findings of the study enable the development of algorithms for timely stroke recognition, facilitating the selection of optimal treatment options for newborns and children of various age groups. Logistic regression serves as the basis for deriving these algorithms, aiming to initiate early treatment and reduce lifelong morbidity and mortality in children. The study outcomes include the formulation of algorithms for timely recognition of newborn stroke, with plans to adopt these algorithms and train a fuzzy classifier-based diagnostic model using machine learning techniques for efficient stroke recognition.

Malaria Parasite Detection in Microscopic Blood Smear Images using Deep Learning Approach

Malaria remains a significant global health concern, posing formidable challenges to healthcare systems. Conventional diagnostic methods rely on manual examination of blood smears under a microscope, a process prone to inefficiencies and subjectivity. Despite prior attempts to leverage Deep Learning algorithms for malaria diagnosis, practical performance has often fallen short. This paper presents a novel machine learning model centred on Convolutional Neural Networks (CNNs) designed to automate the classification and prediction of infected cells in thin blood smears on standard microscope slides. Through rigorous ten-fold cross-validation with 27,558 single-cell images. This paper reviews various image processing techniques employed for the detection of malaria infection in humans, presenting a comparative analysis of these methods

Machine learning applications in craniosynostosis diagnosis and treatment prediction: a systematic review.

Craniosynostosis refers to the premature fusion of one or more of the fibrous cranial sutures connecting the bones of the skull. Machine learning (ML) is an emerging technology and its application to craniosynostosis detection and management is underexplored. This systematic review aims to evaluate the application of ML techniques in the diagnosis, severity assessment, and predictive modeling of craniosynostosis. A comprehensive search was conducted on the PubMed and Google Scholar databases using predefined keywords related to craniosynostosis and ML. Inclusion criteria encompassed peer-reviewed studies in English that investigated ML algorithms in craniosynostosis diagnosis, severity assessment, or treatment outcome prediction. Three independent reviewers screened the search results, performed full-text assessments, and extracted data from selected studies using a standardized form. Thirteen studies met the inclusion criteria and were included in the review. Of the thirteen papers examined on the application of ML to the identification and treatment of craniosynostosis, two papers were dedicated to sagittal craniosynostosis, five papers utilized several different types of craniosynostosis in the training and testing of their ML models, and six papers were dedicated to metopic craniosynostosis. ML models demonstrated high accuracy in identifying different types of craniosynostosis and objectively quantifying severity using innovative metrics such as metopic severity score and cranial morphology deviation. The findings highlight the significant strides made in utilizing ML techniques for craniosynostosis diagnosis, severity assessment, and predictive modeling. Predictive modeling of treatment outcomes following surgical interventions showed promising results, aiding in personalized treatment strategies. Despite methodological diversities among studies, the collective evidence underscores ML's transformative potential in revolutionizing craniosynostosis management.

Recent Advances in Intelligent Algorithms for Fault Detection and Diagnosis.

Fault-finding diagnostics is a model-driven approach that identifies a system's malfunctioning portion. It uses residual generators to identify faults, and various methods like isolation techniques and structural analysis are used. However, diagnostic equipment doesn't measure the remaining signal-to-noise ratio. Residual selection identifies fault-detecting generators. Fault detective diagnostic (FDD) approaches have been investigated and implemented for various industrial processes. However, industrial operations make it difficult to implement FDD techniques. To bridge the gap between theoretical methodologies and implementations, hybrid approaches and intelligent procedures are needed. Future research should focus on improving fault prognosis, allowing for accurate prediction of process failures and avoiding safety hazards. Real-time and comprehensive FDD strategies should be implemented in the age of big data.

Principles of surgery according to the Integral Theory Paradigm (ITP).

A core concept of the Integral Theory System is that "ligaments are for structure; vagina is for function". The vagina and uterus should be conserved. Because the vagina is an organ, its collagen and elastin, which are so necessary for its function, cannot regenerate once they are removed. Removing the uterus involves severing the descending uterine artery, which is the principal blood supply of the proximal part of the uterosacral ligaments (USLs), and so may cause atrophy, which can cause future incontinence problems because of collagen loss after menopause. The diagnostic algorithm guides which of the five pelvic ligaments need repair. Native ligament plication can be adequate for prolapse/symptom cure, but only in premenopausal women. Postmenopausal women are usually collagen deficient and require collagen-creating tapes or wide-bore polyester sutures to restore structural collagen in the ligaments. Of extreme importance, vaginal tissue excision should be avoided, as consequent scarring may cause "tethered vagina syndrome" (TVS). TVS can cause massive uncontrolled urine loss because the scar tissue in the bladder neck area of the vagina can link the more powerful posterior muscles to the anterior, so the posterior urethra wall is forcibly pulled open, when given the signal to close. Instead of vaginal excision, a "concertina" suture technique re-assigns and shrinks excess vaginal tissue to normal anatomy by 6 weeks. In conclusion, the five key surgical principles of the Integral Theory System are: ligaments are for structure, vagina is for function; structure (prolapse) and function (symptoms) are related; repair the structure and you will restore the function; avoid vaginal excision and hysterectomy; create new collagen to reinforce the damaged ligaments.

COMPUTER SIMULATION OF THE DIAGNOSTIC SYSTEM OF BRAKING CIRCUITS OF FREQUENCY-CONTROLLED ASYNCHRONOUS ELECTRIC DRIVES CONVERTERS

This research is essential for improving the reliability and efficiency of frequency-controlled asynchronous electric drives, especially in industrial environments where uninterrupted production processes are critical. The primary goal of the research is to develop a computer model for a brake system diagnostic system that allows for the timely detection of issues and failures in these systems. One of the key aspects of your research is the use of computer modeling, particularly in the MatLab Simulink environment. This enables engineers and researchers to more easily develop and test models, reducing research time and costs. An important element of such a model is the use of logic-time functions and wavelet diagnostics. These methods allow for the analysis of signals from brake systems from different perspectives and the detection of anomalies in their operation. The research also focuses on mathematical models of brake systems that are integrated into computer programs for simulating the operation of electric drives. Analyzing critical parameters and characteristics of brake circuits helps identify potential problems or failures in advance. Diagnostic algorithms based on data obtained from computer models enable the timely determination of the brake system's condition and the necessary decision-making to enhance safety and efficiency in electric drive operation. The results obtained from your research have significant practical importance as they help maintain the reliability and safety of industrial systems at a high level. Brake system diagnostics in frequency-controlled asynchronous electric drives become more accessible and efficient through the use of mathematical models and computer modeling in MatLab Simulink. This contributes to increased productivity and reduced risk of accidents in industrial systems.

Update kidney allograft pathology : Abetter depiction of microvascular inflammation

The Banff Foundation produces recommendations for classifying various lesions in renal allografts. Experts gather to update the classification every other year based on new scientific and clinical evidence. This article presents the most important changes incorporated into the new recommendations after the last Banff conference. The author of this article personally took part in the Banff conference and the subsequent survey, reported on the activities of aBanff working group (peritubular capillaritis) on-site, and contributed to drafting the recently published meeting report. Lesions of antibody-mediated kidney allograft rejection (AMR), especially microvascular inflammation, have been part of the diagnostic algorithm for over 20years. Experts advocated for asimplified AMR algorithm and mindful inclusion of molecular pathological data in the clinicopathological reflection regarding therapeutic decision. Anew, more descriptive diagnostic entity-microvascular inflammation, C4d negative and DSA negative-has been introduced into the AMR category to acknowledge this histological constellation and motivate research into this pathophysiologically and immunologically probably different phenotype. The Banff classification provides astructure for diagnosing kidney transplant pathology. Regular updates serve to adapt to ever-growing knowledge about alloimmunity. Particular challenges are capturing the complexity of various immunological scenarios and ensuring an understandable representation of these in apathology report.

Percutaneous image-guided lumbar decompression and outpatient laminectomy for the treatment of lumbar spinal stenosis: a 2-year Medicare claims benchmark study

BackgroundThis prospective longitudinal study compares outcomes for Medicare beneficiaries receiving outpatient percutaneous image-guided lumbar decompression (PILD) using the mild® procedure to patients undergoing outpatient laminectomy. All patients were diagnosed with lumbar spinal stenosis (LSS) with neurogenic claudication (NC). MethodsAll medical claims for 100 % of Medicare beneficiaries were reviewed, with study subjects identified using Centers for Medicare and Medicaid Research Identifiable Files. Baseline data were extracted individually to allow for longitudinal analysis through two-year follow-up. The index procedure was defined as the first mild or outpatient laminectomy during the enrollment period. The rate of subsequent surgical procedures and incidence of harms were used as study outcomes. ResultsCohorts included 2197 mild and 7416 laminectomy patients. mild patients were significantly older (76.7 years versus 73.4 years, respectively; p < 0.0001), and 57.4 % of mild were female, compared to 43.3 % of laminectomy (p < 0.0001). mild patients presented with significantly more baseline comorbidities compared to laminectomy patients (mean of 5.7 versus 4.8, respectively; p < 0.0001). Subsequent surgical procedure rate of 9.0 % for mild was significantly higher than 5.5 % for laminectomy (p < 0.0001). mild experienced harms at a significantly lower rate than laminectomy (1.9 % versus 5.8 %, respectively; p < 0.0001). The composite rate of subsequent surgical procedures and harms was similar between groups at 10.8 % for mild and 11.0 % for laminectomy. Conclusionsmild can be considered a viable option for treatment of LSS with NC as evidenced by real-world data in this study. At two-years, mild patients experienced fewer harms and underwent more subsequent surgical procedures than laminectomy patients. The higher rate of subsequent surgical procedures for mild may be attributable to its position earlier in the LSS treatment algorithm. The overall rate of harms and subsequent surgical procedures was similar between groups, suggesting that mild should be considered as a treatment option, particularly for older patients with multiple comorbidities.

Update on extraesophageal manifestations of gastroesophageal reflux.

Symptoms/complications related to extraesophageal reflux (EER) are increasingly prevalent presentations and pose significant challenges for clinicians. We summarize and discuss clinical advances and developments in pathophysiology, testing and treatment algorithms of upper/lower airway manifestations of EER. Growing evidence supports likely multifactorial causes of laryngeal symptoms, including EER, oropharyngeal pathologies, allergic conditions, and cognitive-affective processes (brain-larynx interaction). Diagnostic paradigm for laryngopharyngeal reflux (LPR) is shifting towards a personalized approach with noninvasive strategies/prediction tools to risk-stratify patients for upfront reflux testing over empiric acid suppression trials. Management should be multipronged to include antireflux therapies and treatments targeting other causes. Lower airway complications of EER may result in lung dysfunction and poor transplant outcomes. Esophageal symptoms are often absent and routine esophageal/reflux testing to guide timely antireflux therapies may lead to improved outcomes. Modalities that leverage impedance technology may be important, given the potential role of nonacidic reflux. Novel impedance-based metrics such as mean nocturnal baseline impedance and postreflux swallow-induced peristaltic wave index may provide adjunctive diagnostic values. Standardized approach to diagnosis/management of EER should include multidisciplinary care teams and consider different phenotypes, nonreflux contributors, and the complex gut-airway relationships. Prompt antireflux therapies after careful candidate selection may improve outcomes of these airway complications.

THE INFLUENCE OF ATOPY ON CYSTIC FIBROSIS COURSE IN CHILDREN

The relevance of research. The course of cystic fibrosis (CF) depends on the influence of different modifying factors. One of these factors is atopy. The role of atopy in CF course is incompletely determined today and requires further study. The purpose of the study: to improve medical care for patients with CF by clarifying the pathogenetic role of atopy in the disease course. Materials and methods. Analysis of data from a clinical and paraclinical examination of 42 children with CF in the Kharkiv region. Patients were divided into two groups: with an elevated level of total immunoglobulin E (n=19) and with a normal level of this indicator (n=23) to determine the features of CF course depending on the atopy presence. Results and discussion. In the group with elevated and normal levels of total serum IgE, boys were predominant, as in the general population, and accounted for 73.6% and 60.8%, respectively. The first manifestations of CF were represented mainly by intestinal signs in both groups at 68.4% and 73.9% of cases, respectively. Data analysis of the clinical features of CF course in children with elevated level of IgE (severity of lung and liver lesions) revealed results without significant differences between groups. High level of sensitivity to ordinary domestic, food and pollen allergens was not detected in children of group with elevated level of IgE. Patients with CF and atopy were found to have a probable increase in the levels of CD3, IgM, spontaneous NBT; phagocytosis of latex; decreasing in the levels of CD4, IgA compared to the group with a normal level of total IgE. Conclusion. Features of the CF phenotype associated with the atopy were analyzed. The received data can be used when determining the treatment algorithm, taking into account the individual characteristics of the disease course.

Utility of Reticulin Algorithm in Diagnosis of Adrenocortical Tumors: A Re-visit

Utility of Reticulin Algorithm in Diagnosis of Adrenocortical Tumors: A Re-visit

The Relationship of Microsatellite Instability with BRAF and p53 Mutations and Histopathological Parameters in Colorectal Adenocarcinoma.

This study aims to elucidate the associations between microsatellite instability (MSI) status, BRAF mutation, and p53 reactions with pathological parameters and survival outcomes in colorectal carcinoma. MutL homologous 1 (MLH1), Postmeiotic segregation increased 2 (PMS2), MutS homologous 2 (MSH2), MutS homologous 6 (MSH6), BRAF, and p53 antibodies were performed on 130 adenocarcinoma samples, including 65 from the right colon and 65 from the left colon. The relationships of MSI status with BRAF mutation, p53 reaction, clinical and pathological parameters, and survival times were statistically analyzed. A statistically significant relationship was found between MSI and right colon localization, tumor size, histological grade, intraepithelial tumor-infiltrating lymphocytes, Crohn-like lymphocytic reaction, expansive growth pattern, and BRAF mutation (p < 0.05). No significant correlation was found between MSI status and the disease-free or overall survival times (p > 0.05). In colorectal adenocarcinoma, MSI and BRAF mutation are associated with parameters, indicating the host immune response and prognostic histopathological parameters, including tumor size and histological grade. The evaluation of MSI status and BRAF mutation can be particularly informative for predicting the prognosis and guiding the treatment management in poorly differentiated colorectal adenocarcinoma. Understanding the mechanisms of molecular carcinogenesis in colorectal carcinoma and organizing treatment algorithms based on molecular foundations will increase the success of the treatment.

A Novel Surgical Treatment Management Algorithm for Elbow Posterolateral Rotatory Instability (PLRI) Based on the Common Extensor Origin Integrity.

Background: Here, we introduce a comprehensive treatment algorithm for posterolateral rotatory instability (PLRI) of the elbow, a condition affecting elbow mobility. We outline a diagnostic approach and a novel surgical management plan through the arthroscopic surgeon's point of view. Methods: The central focus of this management approach is the integrity of common extensor origin (CEO). High clinical suspicion must be evident to diagnose PLRI. Special clinical and imaging tests can confirm PLRI but sometimes the final confirmation is established during the arthroscopic treatment. The most appropriate treatment is determined by the degree of CEO integrity. Results: The treatment strategy varies with the CEO's condition: intact or minor tears require arthroscopic lateral collateral ligament imbrication, while extensive tears may need plication reinforced with imbrication or, in cases of retraction, a triceps tendon autograft reconstruction of the lateral ulnar collateral ligament alongside CEO repair. These approaches aim to manage residual instability and are complemented using a tailored rehabilitation protocol to optimize functional outcomes. Conclusion: PLRI is a unique clinical condition and should be treated likewise. This algorithm offers valuable insights for diagnosing and treating PLRI, enhancing therapeutic decision-making.

The Gold Standard Diagnosis of Schizophrenia is Counterproductive: Towards Quantitative Research and Diagnostic Algorithmic Rules (RADAR) and their Derived Qualitative Distinct Classes.

Recently, we developed Research and Diagnostic Algorithm Rules (RADAR) to assess the clinical and pathway features of mood disorders. The aims of this paper are to review a) the methodology for developing continuous RADAR scores that describe the clinical and pathway features of schizophrenia, and b) a new method to visualize the clinical status of patients and the pathways implicated in RADAR graphs. We review how to interpret clinical RADAR scores, which serve as valuable tools for monitoring the staging of illness, lifetime suicidal behaviors, overall severity of illness, a general cognitive decline index, and a behavior-cognitive-psychosocial (BCPS) index that represents the "defect"; and b) pathway RADAR scores which reflect various protective (including the compensatory immune- inflammatory system) and adverse (including neuro-immune, neuro-oxidative, and neurotoxic biomarkers) outcome pathways. Using RADAR scores and machine learning, we created new, qualitatively different types of schizophrenia, such as major neurocognitive psychosis and simple psychosis. We also made RADAR graphs, which give us a quick way to compare the patient's clinical condition and pathways to those of healthy controls. We generated a personalized fingerprint for each patient, encompassing various clinical and pathway features of the disorder represented through RADAR graphs. The latter is utilized in clinical practice to assess the clinical condition of patients and identify treatment-required pathways to mitigate the risk of recurrent episodes, worsening BCPS, and increasing staging. The quantitative clinical RADAR scores should be used in schizophrenia research as dependent variables and regressed on the pathway RADAR scores.