Smart Healthcare IoT Applications Using AI

Globally, healthcare professionals strive to diagnose, monitor, and save human lives. An application that advances the medical field to the next level is the need of the hour. Smart healthcare systems using IoT help in the process of monitoring human health by minimizing human intervention. Taking care and monitoring of human health has a significant contribution in declining the mortality rate as well. IoT in healthcare has aided smarter communications and prompt treatment to save lives. Patient data are sensed by sensors/microcontrollers, sent over the internet, stored in the cloud, and received by healthcare professionals during emergencies. Applications of such smart healthcare using IoT are blood glucose meters, medical vehicles, sphygmomanometer, pulse oximeter, Holter monitor, etc. This chapter elucidates several smart healthcare IoT applications using artificial intelligence and cloud computing technology. The chapter also elaborates the importance and functions of various cloud and AI components in designing a smart healthcare application.

A Window Into Functional Communication: Leveraging Naturalistic Speech Samples in Primary Progressive Aphasia

Purpose Naturalistic speech samples should be routinely collected in the assessment of individuals with communication difficulties. However, even when these samples are collected, they are often underutilized. We propose that the analysis of naturalistic speech samples can greatly enhance our understanding and evaluation of the functional impact of primary progressive aphasia (PPA) on communication. First, we review the current practices of evaluating PPA. Second, we provide a framework to optimize the collection, analysis, and interpretation of speech samples to accomplish this goal. In particular, we demonstrate how speech samples can be evaluated for measures of informativeness, the presence of atypical patterns of speech, articulatory rate, and pausing, all of which are helpful metrics in characterizing disordered speech. These factors can be leveraged to identify both the strengths and difficulties an individual may face in everyday communication. Conclusion The collection of naturalistic speech in both clinical and naturalistic settings with typical communication partners is highly recommended to best diagnose, monitor, and inform treatment plans for individuals with PPA.

Laboratory Testing Implications of Risk-Stratification and Management for Improving Clinical Outcomes of COVID-19 Patients

ABSTRACTThe high mortality rate of COVID-19 patients is mainly caused by the progression from mild to critical illness. To identify the key laboratory indicators and stratify high-risk COVID-19 patients with progression to severe/critical illness, we compared 474 moderate patients and 74 severe/critical patients. The laboratory indicators, including lactate dehydrogenase (LDH), monocytes percentage, etc. were significantly higher in the severe/critical patients (P <0.001) and showed a noticeable change at about a week before the diagnosis. Based on these indicators, we constructed a risk-stratification model, which can accurately grade the severity of patients with COVID-19 (accuracy = 0.96, 95% CI: 0.94 - 0.989, sensitivity = 0.98, specificity = 0.84). Also, compared with non-COVID-19 viral pneumonia, we found that COVID-19 had weaker dysfunction to the heart, liver, and kidney. The prognostic model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage to those patients with COVID-19.

Notified dengue deaths in Myanmar (2017-18): profile and diagnosis delays

Background: Complications in dengue usually occur between day four and day six after fever onset. Hence, early diagnosis and haematological monitoring are vital. Among all hospital reported dengue deaths in Myanmar in 2017-18, we assessed the i) patient profile, ii) proportion of patients who arrived with a dengue diagnosis at admission and iii) delays in diagnosis after fever onset. Methods: This was a descriptive study involving secondary data. For all the notified deaths, death investigation forms were not available in prescribed format and therefore, data were extracted from hospital case records. Results: Of 304 deaths, 184 (60.5%) were female and 233 (76.6%) were less than 10 years old. Township level hospitals or below reported 36 deaths (11.8%) and the remaining deaths were from higher level facilities. Dengue was diagnosed before admission in 26 (8.5%) people and 169 (55.6%) were in shock at admission. Of 208 with date of fever onset recorded, the median diagnosis delay was four (interquartile range-IQR: 3, 5) days. Patient level delay (median three days) was a major contributor to the diagnosis delay. Conclusions: Most of the patients who died did not have a diagnosis of dengue before admission. This calls for an urgent review of health system preparedness in peripheral health facilities to suspect, diagnose, monitor, refer and treat dengue in children and patient level factors for better understanding of the reasons of delay. Timely filling of death investigation forms in a prescribed format and quarterly death reviews based on these is recommended.

Poly-d-lysine coated nanoparticles to identify pro-inflammatory macrophages

Identifying pro-inflammatory macrophages (M1) is of immense importance to diagnose, monitor, and treat various pathologies. Here, we present a poly-D-lysine coated nanoparticle for real-time fluorescent labeling of M1 macrophages.

INVASIVE NON-TYPE B HAEMOPHILUS INFLUENZAE DISEASE: REPORT OF EIGHT CASES

ASTRACT Objective: To describe eight cases of invasive non-type b Haemophilus influenzae disease in children admitted to Hospital de Clínicas of Universidade Estadual de Campinas. Cases description: In 2015, there were eight cases of invasive non-type b H. influenzae disease. We tested the ampicillin sensitivity and beta-lactamase production of the strains identified and performed the genotyping. Molecular typing was determined by Pulsed-Field Gel Electrophoresis. Four patients were diagnosed with bacteremia; in two cases, H. influenzae was detected in the pleural fluid, and two patients had meningitis. Patients with comorbidities represented 37.5% of cases. Except for the strain of one patient - not sent to the reference laboratory -, all were ampicillin-sensitive and non-beta-lactamase-producing. Genotyping identified four non-capsular, one type c, and two type a strains. Molecular typing ruled out nosocomial transmission since all serotypes were distinct regarding genotype. Comments: The rise in cases of invasive non-type b H. influenzae infection was real. There was no nosocomial transmission, and we found no justification for the increase. These data indicate the need for surveillance to correctly diagnose, monitor, and understand the spectrum of non-type b H. influenzae disease.

Using Epstein-Barr Viral Load Assays To Diagnose, Monitor, and Prevent Posttransplant Lymphoproliferative Disorder

SUMMARYEpstein-Barr virus (EBV) DNA measurement is being incorporated into routine medical practice to help diagnose, monitor, and predict posttransplant lymphoproliferative disorder (PTLD) in immunocompromised graft recipients. PTLD is an aggressive neoplasm that almost always harbors EBV DNA within the neoplastic lymphocytes, and it is often fatal if not recognized and treated promptly. Validated protocols, commercial reagents, and automated instruments facilitate implementation of EBV load assays by real-time PCR. When applied to either whole blood or plasma, EBV DNA levels reflect clinical status with respect to EBV-related neoplasia. While many healthy transplant recipients have low viral loads, high EBV loads are strongly associated with current or impending PTLD. Complementary laboratory assays as well as histopathologic examination of lesional tissue help in interpreting modest elevations in viral load. Circulating EBV levels in serial samples reflect changes in tumor burden and represent an effective, noninvasive tool for monitoring the efficacy of therapy. In high-risk patients, serial testing permits early clinical intervention to prevent progression toward frank PTLD. Restoring T cell immunity against EBV is a major strategy for overcoming PTLD, and novel EBV-directed therapies are being explored to thwart virus-driven neoplasia.