Contacts

Perhaps all of us will agree on about a Contacts page, is that every website should have one. A Contacts Page like this one you are reading, provides an opportunity to make it easy for you as a visitor to this website-blog to contact me. A contact form provides an opportunity to gather information from visitors like you.I welcome the opportunity to consider your thoughts, concerns, ideas, and questions.If you would like to send a message to me, please take a minute to complete the following contact form, which will provide me with information necessary to process your message (Note: items marked with a red asterisk against any part of the contact form below must be entered to successfully submit your details when contacting me). You will also find on this page the list of contacts who wished to be included in my contacts list. You may contact my contacts from the tabular lists below.


MEDICAL RECORDS PALS MALAYSIA CONTACTS LIST

No.NameMobile No.Email AddressDomicile
1ABDUL MALEK BIN ABU BAKAR+60 6 231 9999 (EXT2201)abdul_malek@hpak.com.my &
ammlkn21@hotmail.com
Malaysia
2ANITA BT. MOHD. YUSOH+60 17 767 0832anita.yusoh@columbiaasia.comMalaysia
3ARUNASALAM PONNAMPALAM+60 13 385 3817ponnaru@gmail.comMalaysia
4BEATRICE VICTORIA BONGbeatrice@srwk.moh.gov.myMalaysia
5BRYAN CHONG AH HOOpec9812@hotmail.comMalaysia
6CHUA CHOON HOW+60 16 773 1200chua.choon.how@monash.eduMalaysia
7DAYANG ROZANA BT. ABANG NAIM+60 13 800 6072dygrozanna@srwk.moh.gov.myMalaysia
8DEVINDER KAURdevin_kaur80@hotmail.comMalaysia
9DR. ABDOOL SAHBOOB KUREEMUN+230 5 776 4097macbool786@yahoo.comMauritius
10DR. CHONG YOK CHING+60 16 259 5165chongyc8@gmail.comMalaysia
11LIM JEW HEANG+60 12 589 2962jhlim@ppg.moh.gov.myMalaysia
12LIM KIM SAY+60 16 762 5873limkimsay48@gmail.comMalaysia
13MAH SOCK KUAN+60 12 682 3155 skmah@nilam.edu.myMalaysia
14MD. NOR BIN ISMAILmdnor1503@yahoo.comMalaysia
15MUHAMAD SARKAN+60 19 267 5177shark_1948@yahoo.comMalaysia
16NOOR KAMILAH BT. ADNANkamilah@dsh.kpjhealth.com.myMalaysia
17NOORUL AIN BT. KARIS+60 12 282 6520ain.karis@princecourt.comMalaysia
18NOR KAMARIAH BT. CHIK+60 12 581 8085norsyam83@yahoo.comMalaysia
19NORAZHANIS BT. MOHD NOOR+60 17 371 3703norazhanismn@sunway.com.myMalaysia
20NURUL ERLEAWATY BT. JAMALUDIN+60 32 296 0413nurul.erleawaty@pantai.com.myMalaysia
21R. RAJENDRAN+60 12 330 8400rajen@mawar.com.myMalaysia
22ROSLAN BIN RAMZI+60 13 817 1135roslanr@srwk.moh.gov.myMalaysia
23SITI HAJAR BT. BAHARIM+60 17 526 7896siti_hajar@moh.gov.myMalaysia
24SIVAGNANAM+60 16 606 3986sivaksmc@pantai.com.myMalaysia
25TAN TIANG CHWEEticitan@gmail.comMalaysia
26TIOW BOK KUANtiowbokkuan@gmail.comMalaysia
27VICTORvictor@srwk.moh.gov.myMalaysia
28YEAP ENG KOOIyeapek@yahoo.comMalaysia
29ZAINUDDIN BIN ALIz_ally2@yahoo.comMalaysia
30EMMIE CHRISTY ANAK UMAR +60 13 355 0109Emmie.christy.umar@ramsaysimedarbyhealth.com Malaysia
31BEH SWEE IM +60 12 403 3231behsi@hlwe.com Malaysia
32FARIZA HUSSIN +60 18 785 2064iza@ish.kpjhealth.com.my Malaysia
33BENARDINE AK PANI +6016 877 9097benardine.kcsh@gmail.com Malaysia
34LAU MING SING +60 10 972 8834ming_sing@kpjsibu.comMalaysia
35NANTHA KUMAR LOGANATHAN +60 12 623 5894nantha1981@gmail.com Malaysia

You can also reach me from all the contact points as I have listed below. Please find the relevant web links from the social media icons found around this website-blog.

Name
:
VIJAYAN RAGAVAN
Mailing
:
25 Jalan Setia 1/10, Taman Setia Indah,
Address
81100 Johor Bahru, Johor, Malaysia
Email
:
vijayanr@mrpalsmy.com
Mobile
:
(60)-12-7280-025
Skype
:
vijayanr54
Facebook
:
http://www.facebook.com/MedicalRecordsPalsMalaysia
LinkedIn
:
my.linkedin.com/pub/vijayanragavan/6/683/9a5
Twitter
:
https://twitter.com/vijayanr

Recent Posts

Voice-to-text medical software using NLP technology

When the doctor sits down with you on your visit, the doctor normally spends a lot of time inputting the how and the why of what’s happening to you, conventionally into a paper-based case note/medical record.

These free text narratives are further aggravated as not all doctors “speak the same way” in note creation and management.

These notes about your condition are rendered not easily extractable in ways that the data can be analyzed by a computer.

The good thing is this unstructured data of free text has given way to more and more ways to digital record-keeping—into the electronic health record systems (EHRs) way, away from the days of trying to decipher doctors’ medical lingo on hand written medical records and medical reports. However, EHRs are as unstructured patient data like its cousin, the paper-based medical record.

Inevitably, EHRs create challenges for doctors and that can be frustrating with additional data input responsibilities often bogged down by form-filling through the many clicks and screens required to navigate their EHRs, as well as they spending additional hours on updating EHRs.

EHRs became more important to be accurate and immediate with the scourge of the COVID-19 pandemic and with an increased reliance on contact-free consultations between doctors and patients.

Ultimately, huge volumes of unstructured patient data continue to be input into EHRs on a daily basis. As healthcare documentation is mostly unstructured, and it therefore goes largely unutilised, since mining and extraction of this data is challenging and resource intensive.

Medical Natural Language Processing (NLP) is steadily proving to be a solution to this challenge, creating new and exciting opportunities for healthcare delivery and patient experience. The adoption of NLP in healthcare is rising because of its recognized potential to search, analyze and interpret mammoth amounts of patient datasets.

Human beings use text and spoken words to fill up the human language with homonyms, homophones, sarcasm, idioms, metaphors, grammar and usage exceptions, variations in sentence structure, as some examples of ambiguities and irregularities as only they understand their usage.

NLP is a branch of artificial intelligence (AI) concerned with giving computers the ability to understand text and spoken words in much the same way we human beings can.

It is the main concept behind translation and personal assistance apps like Google Translate, OK Google, Siri, Cortana, and Alexa.

Without NLP technology using NLP healthcare tools capable of scrubbing large sets of unstructured health data, that data is not in a usable format for modern computer-based algorithms to easily access, extract, and accurately interpret clinical documentation of the actual patient record previously considered buried in text form.

NLP technology services accurately give voice to the unstructured data of the healthcare universe while processing the content of long chart notes of medical records, giving incredible insight into understanding quality, improving methods, and better results for patients that helps determine the disease burden and valuable decision support can be obtained.

Augnito is a voice-to-text medical software using NLP technology hoping  to improve healthcare, but for now specifically developed for the Indian market launched six months ago, and now being used in 24 States in India.

The voice has become the most powerful tool in technology today. Just by talking, the voice is the most natural way of communication for humans. We are able to do sophisticated and important jobs with gadgets like Alexa.

Like the Alexa gadget been able to do sophisticated and important jobs using voice controlled NLP technology, the Augnito software available for a monthly subscription on both Mac and Windows platforms, types out notes that are dictated to and saves it in an editable textual format on a cloud server.

The Augnito voice recognition software has a pre-programmed list of medical terms (its vocabulary database is constantly updated in keeping with doctors’ requirements and feedback), a built-in editor, report templates and keyboard shortcuts that help reduce repetitive typing.

Voice recognition software like Augnito using NLP technology, has the potential to boost a doctor’s productivity at a time of increased online consultations.

  1. Emergency use ICD codes for COVID-19 disease outbreak Leave a reply
  2. Global COVID-19 Clinical Characterization Case Record Form Leave a reply
  3. ICD Coding advice from the WHO for the 2019 novel coronavirus (COVID-19) Leave a reply
  4. ICD-11 2018 version: Part 2 – The ICD-11 Menu Hierarchy Leave a reply