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Reimagining Medical Diagnosis with Chatbots

4 minutes, 51 seconds read

Chatbots are rapidly gaining popularity in the healthcare sector. According to research conducted by Grand View Research, the global chatbot market is expected to reach $1.23 billion by 2025 growing at a CAGR of 24.3%. The current COVID pandemic has caused a lot of stress in the healthcare sector, with hospitals getting swamped with COVID-19 patients and also handling regular consults. 

This has made medical chatbots very attractive, helping in scheduling appointments, custom support, symptom checks, providing nutrition and wellness information, mental therapy, etc. Let’s take a look at how chatbots are transforming the digital transformation in the healthcare sector.

The shift to Medical Chatbots and Telemedicine

Lockdowns and social distancing due to COVID-19 gave a significant boost to digital business models. Organizations had to find ways to keep up the operations, make business continuity plans, and engage the workforce working remotely. Even healthcare providers took to technology such as telemedicine, chatbots, and remote monitoring equipment for patients who were not able to visit doctors in person. 

Many hospitals had been trying to implement telemedicine over the last couple of years, at least for ailments that can do without in-person diagnosis and can be cured by prescribing medicines based on symptoms told by the patient. COVID-19 gave that extra push for telemedicine. 

Another tendency that people have these days is to search for information on Google for self-diagnosis. However, that may not be effective. Therefore, many people are turning towards healthcare chatbots for medical information. 

Multilingual AI chatbot with video for diagnostic services – Hitee.chat

The Role of Chatbots in Medical Diagnosis 

The entire experience from admission to discharge is one of the key differentiators for patients while choosing a healthcare provider. People want quicker services and instant answers to their queries. 

With the coronavirus outbreak, hospitals and clinics are facing additional pressure. It has created a dire need for technology such as medical chatbots to provide better patient experience. 

Currently, there are some chatbots that leverage AI and machine learning to provide diagnoses by using algorithms to run the responses through a database of medical literature available. Let’s take a look at possible situations where chatbots play a crucial role in diagnostics-

  • Reliability: Instead of using a search engine to find answers, people will find chatbots more reliable for medical information. They need to be backed by legitimate medical databases to provide better accuracy.
  • Medical History: Chatbots cannot replace the role of a doctor while diagnosing but it can be of great assistance to them in providing medical history to better diagnose the health issue.
  • Triggering Attention: There are many symptom checking apps and bots available today which are widely used to check symptoms for possible diseases. Even with the nearest possible result in hand, it triggers the patient to a doctors’ visit if the symptoms seem grave. 
  • Support for Healthcare Workers: In case of mild diseases such as common cold, indigestion, minor wounds, etc. Chatbots are of great help as they reduce the workload of health workers who can focus on critical patients. 
  • Ensure Confidentiality: In some cases, patients may not be comfortable to open up to a doctor in person, but finds it easier to answer questions by a chatbot. Especially, when it comes to mental illness. 
  • Availability: Although rare, but there can be cases when medical help is not available physically such as during curfews or lockdowns. In such situations chatbots can be of great help for immediate medical support. 

Prevailing Challenges

Chatbots can provide basic medical information or do a cursory diagnosis of a health problem. However, the biggest challenge with diagnostic chatbots is the accuracy of the output. 

Research by the National Center for Biotechnology Information (NCBI) suggests that computer-based diagnostic support tools can be very beneficial to clinicians. But the effectiveness of 23 symptom checkers reported deficits and only 34% of standard patient evaluations were achieved in the first attempt. 

Unlike actual doctors, chatbots cannot feel the pulse, check the heartbeat or blood pressure, check the body part where the issue is, etc. Patients these days tend to self-diagnose quite often but they may not understand the diagnoses. 

Medical Chatbots can provide the information but can they explain it like a doctor as well? That would be debatable. Not everyone can understand medical jargon. Another issue is the risk of error in diagnosis. Too much dependency on the diagnosis can have steep consequences putting lives at risk. 

Redefining Chatbots in Medical Diagnosis

Currently, the chatbots function primarily through text while chatting with the patient. But in the coming future, it has a huge scope of improvement when combined with videos, images, voice recognition it will provide better information to the chatbot to provide better diagnoses. 

Medical diagnosis chatbot with video – Hitee.chat

Technologies like Natural Language Processing (NLP), machine learning, AI algorithms will enable better processing of the data and help clinicians with quicker diagnosis. It is possible to increase the capability of these chatbots through broader data and technologies. NLP integrated chatbots can also cater to specially-abled patients. 

More usage of diagnostic chatbots will make people take better care of their health. Indeed, there is scope for improvement for chatbots in medical diagnosis. But at the same time, reliability on them is also gradually increasing.

Down the Road

Chatbots in medical diagnosis can act as an aid to clinicians, reduce workload for healthcare workers, provide instant answers, and in some cases, it is a cheaper medium and lesser hassle than to visit a hospital. 

Bots have huge potential to streamline diagnosis. It won’t be a surprise to see chatbots be the first point of contact for medical help. 

We’ve introduced a multilingual AI-powered video chatbot for hospitals, private clinics, and diagnostic services. It can automate appointment bookings, checking symptoms, provide information, answer FAQs and more. You can write to us at hello@mantralabsglobal.com for your specific requirements.

Website: Hitee.chat

To know more about how HealthTech is reshaping the healthcare industry in bringing hospitals to a customer’s doorstep, watch our webinar on Digital Health Beyond COVID-19

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Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

  • What caused downtime during last night’s shift?
  • Was there a delay in maintenance response?
  • Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

  • Reports often arrive late—after downtime, delays, or defects have occurred.
  • Disconnected data across ERP, MES, and sensors limits cross-functional insights.
  • Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

  • Centralized Data Hub with real-time access to critical business insights.
  • Automated report generation with data ingestion and processing.
  • Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios. 
  • Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

  • Faster response to machine alerts
  • Quality incidents traced to specific operator workflows
  • 4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers. 

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

AspectWhat You Should Know
1. Why Static Reports Fall ShortDelayed insights after issues occur
Disconnected systems (ERP, MES, sensors)
No real-time alerts or embedded decision logic
2. What Real-Time Dashboards EnableTrack OEE and downtime in real-time
Predictive maintenance using sensor data
Dynamic inventory heat maps
Quality linked to operators
3. Dashboards That Drive ActionRole-based views (operator to CEO)
Embedded alerts like “Line 4 down for 15+ mins”
Drilldowns from plant-level to machine-level
4. What Powers These DashboardsUnified Data Lakehouse (ERP + IoT + MES)
Real-time ETL pipelines
Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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